Int J Comput Dent. 2025 Apr 24;0(0):0. doi: 10.3290/j.ijcd.b6173229. Online ahead of print.

ABSTRACT

AIM: Panoramic radiography is a frequently utilized imaging technique in standard dental examinations and provides many advantages. In this context, studies have been conducted to develop tools to assist physicians in clinical practice by using deep learning models to interpret panoramic radiography images. However, studies in the existing literature have generally addressed these conditions separately and studies that develop a multiclass diagnostic charting model that can detect and segment all these conditions are very limited. Therefore, the aim of this study to develop a deep learning model that can accurately evaluate and segment various dental issues and anatomical structures in panoramic radiographs obtained from different radiography devices and settings.

MATERIALS AND METHODS: Panoramic radiographs were labelled for 33 different conditions in the categories of dental problems, dental restorations, dental implants, anatomical landmarks, periodontal conditions, jaw pathologies and periapical lesions. A YOLO-v8 model was employed to develop an artificial intelligence model for each labelling. A confusion matrix was utilised to successfully evaluate the developed models.

RESULTS: The algorithm achieved a precision value of 0.99-1 in accurately detecting various dental features, such as adult tooth numbering, filling, dental implants, dental pulp, root canal filling, mandibular canal, mandibular condyle, mandible, and pharyngeal airway. With respect to sensitivity, the adult tooth numbering, dental implants, mandibular canal, maxillary sinus, mandibular condyle, angulus mandible, nasal septum, mandible, and hard palate showed the highest values of 0.99-1. The F1-score reached the highest value of 0.99-1 for the root canal filling, adult tooth numbering, dental implants, mandibular canal, mandibular condyle, angulus mandible, mandible, and pharyngeal airway.

CONCLUSION: Artificial intelligence based on convolutional neural networks has a remarkable ability to detect different conditions observed in regular clinical evaluations in panoramic radiographs, displaying excellent performance. Based on these findings, it can be confidently stated that deep learning-based models has great potential to improve routine clinical practices for physicians.

PMID:40272192 | DOI:10.3290/j.ijcd.b6173229

J Dent Res. 2025 Apr 24:220345251322508. doi: 10.1177/00220345251322508. Online ahead of print.

ABSTRACT

Lymph node (LN) metastasis is a prevalent cause of recurrence in oral squamous cell carcinoma (OSCC). However, accurately identifying metastatic LNs (LNs+) remains challenging. This prospective clinical study aims to test the effectiveness of our convolutional neural network (CNN) model for identifying OSCC cervical LN+ in contrast-enhanced computed tomography (CECT) in clinical practice. A CNN model was developed and trained using a dataset of 8,380 CECT images from previous OSCC patients. It was then prospectively validated on 17,777 preoperative CECT images from 354 OSCC patients between October 17, 2023, and August 31, 2024. The model's predicted LN results were provided to the surgical team without influencing surgical or treatment plans. During surgery, the predicted LN+ were identified and sent for separate pathological examination. The accuracy of the model's predictions was compared with those of human experts and verified against pathology reports. The capacity of the model to assist radiologists in LN+ diagnosis was also assessed. The CNN model was trained over 40 epochs and successfully validated after each. Compared with human experts (2 radiologists, 2 surgeons, and 2 students), the CNN model achieved higher sensitivity (81.89% vs. 81.48%, 46.91%, 50.62%), specificity (99.31% vs. 99.15%, 98.36%, 96.27%), LN+ accuracy (76.19% vs. 75.43%, P = 0.854; 40.64%, P < 0.001; 37.44%, P < 0.001), and clinical accuracy (86.16% vs. 83%, 61%, 56%). With the model's assistance, the radiologists surpassed both the previous predictive results without the model's support and the model's performance alone. The CNN model demonstrated an accuracy comparable to that of radiologists in identifying, locating, and predicting cervical LN+ in OSCC patients. Furthermore, the model has the potential to assist radiologists in making more accurate diagnoses.

PMID:40271993 | DOI:10.1177/00220345251322508

Materials (Basel). 2025 Mar 29;18(7):1554. doi: 10.3390/ma18071554.

ABSTRACT

Optical sensing technologies play a crucial role in various fields such as biology, medicine, and food safety by measuring changes in material properties, such as the refractive index, light absorption, and scattering. Dielectric metasurfaces, with their subwavelength-scale geometric features and the ability to achieve high-quality-factor (Q-value) resonances through specific meta-atom designs, offer a new avenue for achieving faster and more sensitive material detection. The resonant wavelength, as one of the key indicators in meta-atom design, is usually determined using traditional solving methods such as electromagnetic simulations, which, although capable of providing high-precision prediction results, suffer from slow computational speed and long processing times. To address this issue, this paper proposes a forward prediction network for the amplitude spectrum of dielectric metasurfaces. Test results demonstrated that the mean square error of this network was consistently less than 10-3, and the neural network required less than 1 s, indicating its high-precision prediction capability. Furthermore, we employed transfer learning to apply this network to predict the near-infrared transmission spectra of high-Q-value resonant dielectric metasurfaces, achieving significant effectiveness. This method greatly enhanced the efficiency of metasurface design, and the designed network could serve as a universal backbone model for the forward prediction of spectral responses for other types of dielectric metasurfaces.

PMID:40271794 | DOI:10.3390/ma18071554

Materials (Basel). 2025 Mar 25;18(7):1448. doi: 10.3390/ma18071448.

ABSTRACT

Carbon fiber-reinforced polymer (CFRP) laminates are widely used in aerospace, automotive, and infrastructure industries due to their high strength-to-weight ratio. However, defect detection in CFRP remains challenging, particularly in low signal-to-noise ratio (SNR) conditions. Conventional segmentation methods often struggle with noise interference and signal variations, leading to reduced detection accuracy. In this study, we evaluate the impact of thermal image preprocessing on improving defect segmentation in CFRP laminates inspected via pulsed thermography. Polynomial approximations and first- and second-order derivatives were applied to refine thermographic signals, enhancing defect visibility and SNR. The U-Net architecture was used to assess segmentation performance on datasets with and without preprocessing. The results demonstrated that preprocessing significantly improved defect detection, achieving an Intersection over Union (IoU) of 95% and an F1-Score of 99%, outperforming approaches without preprocessing. These findings emphasize the importance of preprocessing in enhancing segmentation accuracy and reliability, highlighting its potential for advancing non-destructive testing techniques across various industries.

PMID:40271635 | DOI:10.3390/ma18071448

Mol Ecol. 2025 Apr 24:e17773. doi: 10.1111/mec.17773. Online ahead of print.

ABSTRACT

The process of domestication has altered many phenotypes. Selection on these phenotypes has long been hypothesised to indirectly select for increases in the genome-wide recombination rate. This hypothesis is potentially consistent with theory on the evolution of the recombination rate, but empirical support has been unclear. We review relevant theory, lab-based experiments, and data comparing recombination rates in wild progenitors and their domesticated counterparts. We utilise population sequencing data and a deep learning method to infer genome-wide recombination rates for new comparisons of chicken/red junglefowl, sheep/mouflon, and goat/bezoar. We find evidence of increased recombination in domesticated goats compared to bezoars but more mixed results in chicken and generally decreased recombination in domesticated sheep compared to mouflon. Our results add to a growing body of literature in plants and animals that finds no consistent evidence of an increase in genome-wide recombination with domestication.

PMID:40271548 | DOI:10.1111/mec.17773

Front Plant Sci. 2025 Apr 9;16:1545216. doi: 10.3389/fpls.2025.1545216. eCollection 2025.

ABSTRACT

With the continuous advancement of modern agricultural technologies, the demand for precision fruit-picking techniques has been increasing. This study addresses the challenge of accurate recognition and harvesting of winter peaches by proposing a novel recognition model based on the residual network (ResNet) architecture-WinterPeachNet-aimed at enhancing the accuracy and efficiency of winter peach detection, even in resource-constrained environments. The WinterPeachNet model achieves a comprehensive improvement in network performance by integrating depthwise separable inverted bottleneck ResNet (DIBResNet), bidirectional feature pyramid network (BiFPN) structure, GhostConv module, and the YOLOv11 detection head (v11detect). The DIBResNet module, based on the ResNet architecture, introduces an inverted bottleneck structure and depthwise separable convolution technology, enhancing the depth and quality of feature extraction while effectively reducing the model's computational complexity. The GhostConv module further improves detection accuracy by reducing the number of convolution kernels. Additionally, the BiFPN structure strengthens the model's ability to detect objects of different sizes by fusing multi-scale feature information. The introduction of v11detect further optimizes object localization accuracy. The results show that the WinterPeachNet model achieves excellent performance in the winter peach detection task, with P = 0.996, R = 0.996, mAP50 = 0.995, and mAP50-95 = 0.964, demonstrating the model's efficiency and accuracy in the winter peach detection task. The high efficiency of the WinterPeachNet model makes it highly adaptable in resource-constrained environments, enabling effective object detection at a relatively low computational cost.

PMID:40271441 | PMC:PMC12014684 | DOI:10.3389/fpls.2025.1545216

Gigascience. 2025 Jan 6;14:giaf028. doi: 10.1093/gigascience/giaf028.

ABSTRACT

We introduce RWRtoolkit, a multiplex generation, exploration, and statistical package built for R and command-line users. RWRtoolkit enables the efficient exploration of large and highly complex biological networks generated from custom experimental data and/or from publicly available datasets, and is species agnostic. A range of functions can be used to find topological distances between biological entities, determine relationships within sets of interest, search for topological context around sets of interest, and statistically evaluate the strength of relationships within and between sets. The command-line interface is designed for parallelization on high-performance cluster systems, which enables high-throughput analysis such as permutation testing. Several tools in the package have also been made available for use in reproducible workflows via the KBase web application.

PMID:40272882 | DOI:10.1093/gigascience/giaf028

Probiotics Antimicrob Proteins. 2025 Apr 24. doi: 10.1007/s12602-025-10549-8. Online ahead of print.

ABSTRACT

The rise of antimicrobial-resistant infections highlights the need for novel therapeutic strategies. Class IIb microcins, a subclass of ribosomally synthesized bacteriocins, play a significant role in modulating bacterial communities by targeting iron acquisition systems in competitive environments, such as the gastrointestinal tract. In this study, we describe and characterize Ec W, a novel class IIb microcin from Escherichia coli strain NCTC10444. This strain is the first known to harbor two homologs of the class IIb microcin biosynthesis cluster and to encode four class IIb microcins in its genome. Sequence analysis revealed that Ec W shows similarity to class IIb microcin Gq W, extending the known repertoire of this microcin class to 18. Heterologous expression and inhibition assays demonstrated potent antimicrobial activity of Ec W against numerous enteric pathogens from the Enterobacteriaceae family, including drug-resistant and hypervirulent strains of E. coli and Klebsiella pneumoniae. These findings suggest that Ec W holds substantial promise as an antimicrobial agent, providing a potential alternative to traditional antibiotics for combating multidrug-resistant pathogens. This study emphasizes the importance of exploring microcins as a novel strategy to tackle the growing threat of infections caused by multidrug-resistant bacteria.

PMID:40272760 | DOI:10.1007/s12602-025-10549-8

Inflamm Res. 2025 Apr 24;74(1):69. doi: 10.1007/s00011-025-02036-1.

ABSTRACT

BACKGROUND: Due to the possible influence of inflammation and gut microbiota in cancers.

METHODS: Fc gamma receptor IIb deficient (FcGRIIb-/-) and cyclic GMP-AMP synthase deficient (cGAS-/-) mice, the model with hyperinflammation and hypo-inflammation, respectively, were subcutaneously injected with MC38 cells (a murine colon cancer cell line).

RESULTS: As such, the tumor burdens were most prominent in cGAS-/- mice, while FcGRIIb-/- mice demonstrated the least tumor sizes compared with wild-type (WT). Intra-tumoral mononuclear cells of FcGRIIb-/- (hematoxylin and eosin staining) were more prominent than other groups with the most dominant CD86-positive cells (mostly M1 proinflammatory macrophages) and the least CD206-positive cells (mostly M2 anti-inflammatory macrophages). While fecal microbiome analysis demonstrated a subtle difference among mouse strains with tumors at 24 days post-cancer injection, serum cytokines (TNF-α, IL-6, IL-1α, IFN-β, IFN-γ, IL-23, IL-12p70, GM-CSF, IL-27, and IL-17A) (fluorescence-encoded bead multiplex assay) and the expansion of immune cells in the spleens of FcGRIIb-/- mice (flow cytometry) were more prominent than others. With bone marrow-derived macrophages, prominent M1 (LPS) and M2 polarization (IL4 and cancer supernatant) in FcGRIIb-/- and cGAS-/- macrophages, respectively, were demonstrated using polymerase chain reaction and flow cytometry. The most prominent tumoricidal activity (percentage of F4/80-negative flexible780 viable dye-positive cells using flow cytometry) of LPS-stimulated FcGRIIb-/- macrophages compared with other groups supported dominant pro-inflammatory characteristics of FcGRIIb-/- macrophages.

CONCLUSIONS: In conclusion, the protective and promoting effects of FcGRIIb-/- and cGAS-/- mice, respectively, against cancers are partly related to macrophage functions with a subtle correlation to fecal microbiota, and FcGRIIb inhibitors and cGAS enhancers might be helpful for cancer adjuvant treatment.

PMID:40272597 | DOI:10.1007/s00011-025-02036-1

Clin Chem. 2025 Apr 24:hvaf043. doi: 10.1093/clinchem/hvaf043. Online ahead of print.

ABSTRACT

BACKGROUND: In 2009, the Minimum Information for Publication of Quantitative Real-Time PCR Experiments (MIQE) guidelines established standards for the design, execution, and reporting of quantitative PCR (qPCR) in research. The expansion of qPCR into numerous new domains has driven the development of new reagents, methods, consumables, and instruments, requiring revisions to best practices that are tailored to the evolving complexities of contemporary qPCR applications.

CONTENT: Transparent, clear, and comprehensive description and reporting of all experimental details are necessary to ensure the repeatability and reproducibility of qPCR results. These revised MIQE guidelines reflect recent advances in qPCR technology, offering clear recommendations for sample handling, assay design, and validation, along with guidance on qPCR data analysis. Instrument manufacturers are encouraged to enable the export of raw data to facilitate thorough analyses and re-evaluation by manuscript reviewers and interested researchers. The guidelines emphasize that quantification cycle (Cq) values should be converted into efficiency-corrected target quantities and reported with prediction intervals, along with detection limits and dynamic ranges for each target, based on the chosen quantification method. Additionally, best practices for normalization and quality control are outlined and reporting requirements have been clarified and streamlined. The aim is to encourage researchers to provide all necessary information without undue burden, thereby promoting more rigorous and reproducible qPCR research.

SUMMARY: Building on the collaborative efforts of an international team of researchers, we present updates, simplifications, and new recommendations to the original MIQE guidelines, designed to maintain their relevance and applicability in the context of emerging technologies and evolving qPCR applications.

PMID:40272429 | DOI:10.1093/clinchem/hvaf043

Nucleic Acids Res. 2025 Apr 22;53(8):gkaf329. doi: 10.1093/nar/gkaf329.

ABSTRACT

Inverted repeats are repetitive elements that can form hairpin and cruciform structures. They are linked to genomic instability; however, they also have various biological functions. Their distribution differs markedly across taxonomic groups in the tree of life, and they exhibit high polymorphism due to their inherent genomic instability. Advances in sequencing technologies and declined costs have enabled the generation of an ever-growing number of complete genomes for organisms across taxonomic groups in the tree of life. However, a comprehensive database encompassing inverted repeats across diverse organismal genomes has been lacking. We present invertiaDB, the first comprehensive database of inverted repeats spanning multiple taxa, featuring repeats identified in the genomes of 118 101 organisms across all major taxonomic groups. For each organism, we derived inverted repeats with arm lengths of at least 10 bp, spacer lengths up to 8 bp, and no mismatches in the arms. The database currently hosts 34 330 450 inverted repeat sequences, serving as a centralized, user-friendly repository to perform searches and interactive visualizations, and download existing inverted repeat data for independent analysis. invertiaDB is implemented as a web portal for browsing, analyzing, and downloading inverted repeat data. invertiaDB is publicly available at https://invertiadb.netlify.app/homepage.html.

PMID:40272360 | DOI:10.1093/nar/gkaf329

Microscopy (Oxf). 2025 Apr 24:dfaf020. doi: 10.1093/jmicro/dfaf020. Online ahead of print.

ABSTRACT

Genome-wide profiling of gene expression levels in cells, such as transcriptomics and proteomics, is a powerful experimental approach in modern biology, allowing not only efficient exploration of the genetic elements responsible for biological phenomena of interest, but also characterization of the global constraints behind plastic phenotypic changes of cells that accompany large-scale remodeling of omics profiles. To understand how individual cells change their molecular profiles to achieve specific phenotypic changes in phenomena such as differentiation, cancer metastasis and adaptation, it is crucial to characterize the dynamics of cellular phenotypes and omics profiles simultaneously at the single-cell level. Especially in the last decade, significant technical progress has been made in the in situ identification of omics profiles of cells on the microscope. However, most approaches still remain destructive and cannot unravel the post-measurement dynamics. In recent years, Raman spectroscopy-based methods for omics inference have emerged, allowing the characterization of genome-wide molecular profile dynamics in living cells. In this review, we give a brief overview of the recent development of imaging-based omics profiling methods. We then present the approach to infer omics profiles from single-cell Raman spectra. Since Raman spectra can be obtained from living cells in a non-destructive and non-staining manner, this method may open the door to live-cell omics.

PMID:40271815 | DOI:10.1093/jmicro/dfaf020

Nucleic Acids Res. 2025 Apr 24:gkaf335. doi: 10.1093/nar/gkaf335. Online ahead of print.

ABSTRACT

The Bakta command line application is widely used and one of the most established tools for bacterial genome annotation. It balances comprehensive annotation with computational efficiency via alignment-free sequence identifications. However, the usage of command line software tools and the interpretation of result files in various formats might be challenging and pose technical barriers. Here, we present the recent updates on the Bakta web server, a user-friendly web interface for conducting and visualizing annotations using Bakta without requiring command line expertise or local computing resources. Key features include interactive visualizations through circular genome plots, linear genome browsers, and searchable data tables facilitating the interpretation of complex annotation results. The web server generates standard bioinformatics outputs (GFF3, GenBank, EMBL) and annotates diverse genomic features, including coding sequences, non-coding RNAs, small open reading frames (sORFs), and many more. The development of an auto-scaling cloud-native architecture and improved database integration led to substantially faster processing times and higher throughputs. The system supports FAIR principles via extensive cross-reference links to external databases, including RefSeq, UniRef, and Gene Ontology. Also, novel features have been implemented to foster sharing and collaborative interpretation of results. The web server is freely available at https://bakta.computational.bio.

PMID:40271661 | DOI:10.1093/nar/gkaf335

iScience. 2025 Mar 26;28(5):112167. doi: 10.1016/j.isci.2025.112167. eCollection 2025 May 16.

ABSTRACT

Dormant lung adenocarcinoma (LUAD) cells in the bone microenvironment can re-emerge as metastatic disease through osteoclast interactions. Using a 3D dormancy model and a mouse bone metastasis model, this study reveals that arachidonic acid (AA) is the initiating molecule transferred from osteoclasts to dormant LUAD cells, triggering their activation. Dormant LUAD cells uptake AA through CD36, which activates the PPARγ-ANGPTL4 pathway and activates tumor cells. There is a dose-response relationship in the activation effect of AA, and inhibiting AA metabolism prevents this reactivation. The study also finds that the serum levels of AA and ANGPTL4 are significantly elevated in patients with clinical bone metastases compared to those without. This research confirms that osteoclasts transmit AA via the CD36-PPARγ-ANGPTL4 axis to activate dormant LUAD cells, suggesting that AA and ANGPTL4 may serve as valuable biomarkers and potential clinical applications in treatment and prediction of LUAD bone metastasis.

PMID:40271019 | PMC:PMC12018030 | DOI:10.1016/j.isci.2025.112167

Front Immunol. 2025 Apr 9;16:1509805. doi: 10.3389/fimmu.2025.1509805. eCollection 2025.

ABSTRACT

INTRODUCTION: Uveitis accounts for up to 25% of global legal blindness and involves intraocular inflammation, classifed as infectious or non-infectious. Its complex pathophysiology includes dysregulated cytokines, particularly interferons (IFNs). However, the global signature of type I, II, and III interferon-regulated genes (Interferome) remains largely uncharacterized in uveitis.

METHODS: In this study, we conducted an integrative systems biology analysis of blood transcriptome data from 169 non-infectious uveitis patients (56 isolated uveitis, 113 systemic disease-associated uveitis) and 82 healthy controls.

RESULTS: Modular co-expression analysis identified distinct cytokine signaling networks, emphasizing interleukin and interferon pathways. A meta-analysis revealed 110 differentially expressed genes (metaDEGs) in isolated uveitis and 91 in systemic disease-associated uveitis, predominantly linked to immune responses. The Interferome database confirmed a predominance of type I and II IFN signatures in both groups. Pathway enrichment analysis highlighted inflammatory responses, including cytokine production (IL-8, IL1-β, IFN-γ, β, and α) and toll-like receptor signaling (TLR4, TLR7, TLR8, CD180). Principal component analysis emphasized the IFN signature's discriminative power, particularly in systemic disease-associated uveitis. Machine learning identified IFN-associated genes as robust predictors, while linear discriminant analysis pinpointed CCR2, CD180, GAPT, and PTGS2 as key risk factors in isolated uveitis and CA1, SIAH2, and PGS in systemic disease-associated uveitis.

CONCLUSION: These findings highlight IFN-driven imune dysregulation and potential molecular targets for precision therapies in uveitis.

PMID:40270958 | PMC:PMC12014655 | DOI:10.3389/fimmu.2025.1509805

Front Public Health. 2025 Apr 9;13:1459060. doi: 10.3389/fpubh.2025.1459060. eCollection 2025.

ABSTRACT

Nowadays, heavy metal (HM) contamination and their ecological risk in coastal sediments are global issues. This research provides insight into the heavy metals' contamination, source apportionment, and potential ecological risks in the surface sediments of the Xiang-Shan wetland in Taiwan, which is undergoing rapid economic development, mainly by the semiconductor industries. The levels of twelve metals and total organic matter (TOM) were measured in 44 samples of surface sediment during the spring and winter seasons of 2022. Subsequently, the single and comprehensive pollution indices were assessed. The findings showed that the average of HM contents exhibited a descending sequence of Al > Fe > Mn > Zn > Co > Ga > Cr > Cu > In > Ni > Pb = Cd during both seasons. The E f , I geo , and PI showed that the majority of sediment samples were uncontaminated to heavily contaminated by Fe, Al, Zn, Cu, Mn, Cr, Ni, Co and Ga, and extremely contaminated by In. Moreover, PLI and mC deg unveiled that the surface sediments of DJ, OB, and KY stations were strongly or extremely polluted. PERI revealed that the sediment shows minimal to moderate ecological risk. The findings of multivariate analyses suggested that Fe, Al, Cu, Zn, and Ni derived from natural sources, while Ga, In, Co, Cr, and Mn originated from both anthropogenic and natural origins. Hence, it is critical that HM contamination, particularly Co, In, and Ga, be continuously monitored in the study area. Our data provide significant insights for more effective prevention and evaluation of HM contamination in the aquatic-sedimentary ecosystems of Taiwan.

PMID:40270744 | PMC:PMC12014647 | DOI:10.3389/fpubh.2025.1459060

MicroPubl Biol. 2025 Apr 8;2025. doi: 10.17912/micropub.biology.001567. eCollection 2025.

ABSTRACT

We examined the effects of X-ray irradiation on Xenopus laevis , focusing on pre- and post-fertilization exposure. We applied X-ray doses of 10, 50, 100, 250, and 500 Gy. Fifty percent of the 360 eggs irradiated at 250 Gy failed to fertilize, while fertilized eggs developed normally until the gastrula stage. Doses ranging from 10 to 250 Gy caused developmental anomalies. High mortality rates were observed at doses of 100 to 500 Gy. Post-fertilization irradiation at 50 to 100 Gy resulted in 100% lethality, while exposure to 10 Gy led to only 13% lethality, although both exposure levels produced similar types of developmental anomalies compared to pre-fertilization irradiation. This study highlights how the timing and intensity of exposure critically affect embryo viability, especially during the sensitive stages of fertilization and gastrulation. We establish the necessary and sufficient dosage to further investigate the molecular mechanisms of X-ray damage to DNA and protein.

PMID:40270682 | PMC:PMC12015645 | DOI:10.17912/micropub.biology.001567

Front Mol Biosci. 2025 Apr 9;12:1557835. doi: 10.3389/fmolb.2025.1557835. eCollection 2025.

ABSTRACT

The human protein kinome is a group of over 500 therapeutically relevant kinases. Exemplified by over 10,000 phosphorylated sites reported in global phosphoproteomes, kinases are also highly regulated by phosphorylation. Currently, 1008 phosphorylated sites in 273 kinases are associated with their regulation of activation/inhibition, and a few in 30 kinases are associated with altered activity. Phosphorylated sites in 196 kinases are related to other molecular functions such as localization and protein interactions. Over 8,000 phosphorylated sites, including all those in 517 kinases are unassigned to any functions. This imposes a significant bias and challenge for the effective analysis of global phosphoproteomics datasets. Hence, we derived a set of stably and frequently detected phosphorylated sites (representative phosphorylated sites) across diverse experimental conditions annotated in the PhosphoSitePlus database and presumed them to be relevant to the human kinase regulatory network. Analysis of these representative phosphorylated sites led to the classification of 449 kinases into four distinct categories (kinases with phosphorylated sites apportioned (PaKD) and enigmatic (PeKD), and those with predominantly within kinase domain (PiKD) and outside kinase domain (PoKD)). Knowledge-based functional analysis and sequence conservation across the family/subfamily identified phosphorylated sites unique to specific kinases that could contribute to their unique functions. This classification of representative kinase phosphorylated sites enhance our understanding of prioritized validation and provides a novel framework for targeted phosphorylated site enrichment approaches. Phosphorylated sites in kinases associated with dysregulation in diseases were frequently located outside the kinase domain, and suggesting their regulatory roles and opportunities for phosphorylated site-directed therapeutic approaches.

PMID:40270594 | PMC:PMC12015135 | DOI:10.3389/fmolb.2025.1557835

Bioact Mater. 2025 Apr 14;50:246-272. doi: 10.1016/j.bioactmat.2025.04.008. eCollection 2025 Aug.

ABSTRACT

We produced a microstructured, electroconductive and nano-functionalized drug eluting cardiac patch (MENDEP) designed to attract endogenous precursor cells, favor their differentiation and counteract adverse ventricular remodeling in situ. MENDEP showed mechanical anisotropy and biaxial strength comparable to porcine myocardium, reduced impedance, controlled biodegradability, molecular recognition ability and controlled drug release activity. In vitro, cytocompatibility and cardioinductivity were demonstrated. Migration tests showed the chemoattractive capacity of the patches and conductivity assays showed unaltered cell-cell interactions and cell beating synchronicity. MENDEP was then epicardially implanted in a rat model of ischemia/reperfusion (I/R). Histological, immunofluorescence and biomarker analysis indicated that implantation did not cause damage to the healthy myocardium. After I/R, MENDEP recruited precursor cells into the damaged myocardium and triggered their differentiation towards the vascular lineage. Under the patch, the myocardial tissue appeared well preserved and cardiac gap junctions were correctly distributed at the level of the intercalated discs. The fibrotic area measured in the I/R group was partially reduced in the patch group. Overall, these results demonstrate that MENDEP was fully retained on the epicardial surface of the left ventricle over 4-week implantation period, underwent progressive vascularization, did not perturb the healthy myocardium and showed great potential in repairing the infarcted area.

PMID:40270551 | PMC:PMC12017858 | DOI:10.1016/j.bioactmat.2025.04.008

Future Oncol. 2025 Apr 24:1-11. doi: 10.1080/14796694.2025.2495543. Online ahead of print.

ABSTRACT

AIM: The present study assessed the incidence of drug-induced interstitial lung disease (ILD) recurrence among breast cancer patients who underwent rechallenge with cancer-directed therapy.

MATERIALS & METHODS: Japanese insurance claims data and the Diagnosis Procedure Combination database (2009-2022) involving 81,601 patients were analyzed to evaluate 1,042 breast cancer patients who developed ILD. Of these, 566 patients underwent cancer-directed therapy rechallenge, and 42.1% of them were re-challenged with the same therapeutic regimen that caused the initial ILD.

RESULTS: ILD recurrence was observed in 18.9% of the patients, with a median recurrence time of 40 days. The drugs most commonly causing ILD were cytotoxic agents, and those most frequently used for rechallenge were cytotoxic agents.

CONCLUSION: A notable ILD recurrence rate was observed in breast cancer patients after a cancer-directed therapy rechallenge, highlighting the need for cautious treatment planning and personalised strategies to balance cancer control while mitigating ILD risk.

PMID:40272014 | DOI:10.1080/14796694.2025.2495543