Mol Cell Proteomics. 2025 Feb 5:100924. doi: 10.1016/j.mcpro.2025.100924. Online ahead of print.

ABSTRACT

Citrullination is a critical yet understudied post-translational modification (PTM) implicated in various biological processes. Exploring its role in health and disease requires a comprehensive understanding of the prevalence of this PTM at a proteome-wide scale. Although mass spectrometry has enabled the identification of citrullination sites in complex biological samples, it faces significant challenges, including limited enrichment tools and a high rate of false positives due to the identical mass with deamidation (+0.9840 Da) and errors in monoisotopic ion selection. These issues often necessitate manual spectrum inspection, reducing throughput in large-scale studies. In this work, we present a novel data analysis pipeline that incorporates the deep learning model Prosit-Cit into the MS database search workflow to improve both the sensitivity and precision of citrullination site identification. Prosit-Cit, an extension of the existing Prosit model, has been trained on ∼53,000 spectra from ∼2,500 synthetic citrullinated peptides and provides precise predictions for chromatographic retention time and fragment ion intensities of both citrullinated and deamidated peptides. This enhances the accuracy of identification and reduces false positives. Our pipeline demonstrated high precision on the evaluation dataset, recovering the majority of known citrullination sites in human tissue proteomes and improving sensitivity by identifying up to 14 times more citrullinated sites. Sequence motif analysis revealed consistency with previously reported findings, validating the reliability of our approach. Furthermore, extending the pipeline to a tissue proteome dataset of the model plant Arabidopsis thaliana enabled the identification of ∼200 citrullination sites across 169 proteins from 30 tissues, representing the first large-scale citrullination mapping in plants. This pipeline can be seamlessly applied to existing proteomics datasets, offering a robust tool for advancing biological discoveries and deepening our understanding of protein citrullination across species.

PMID:39921205 | DOI:10.1016/j.mcpro.2025.100924

Int J Radiat Oncol Biol Phys. 2025 Feb 5:S0360-3016(25)00085-9. doi: 10.1016/j.ijrobp.2025.01.028. Online ahead of print.

ABSTRACT

PURPOSE: The integration of advanced imaging and artificial intelligence (AI) technologies in radiotherapy has revolutionized cancer treatment by enhancing precision and adaptability. This study introduces a novel Dual Energy CT (DECT)-Guided Intelligent Radiation Therapy (DEIT) platform designed to streamline and optimize the radiotherapy process. The DEIT system combines DECT, a newly designed dual-layer multi-leaf collimator, deep learning algorithms for auto-segmentation, automated planning and QA capabilities.

METHODS: The DEIT system integrates an 80-slice CT scanner with an 87 cm bore size, a linear accelerator delivering four photon and five electron energies, and a flat panel imager optimized for MV Cone Beam CT acquisition. A comprehensive evaluation of the system's accuracy was conducted using end-to-end tests. Virtual monoenergetic CT images and electron density images of the DECT were generated and compared on both phantom and patient. The system's auto-segmentation algorithms were tested on five cases for each of the 99 organs at risk, and the automated optimization and planning capabilities were evaluated on clinical cases.

RESULTS: The DEIT system demonstrated systematic errors of less than 1 mm for target localization. DECT reconstruction showed electron density mapping deviations ranging from -0.052 to 0.001, with stable HU consistency across monoenergetic levels above 60 keV, except for high-Z materials at lower energies. Auto-segmentation achieved dice similarity coefficients above 0.9 for most organs with inference time less than 2 seconds. Dose-volume histogram (DVH) comparisons showed improved dose conformity indices and reduced doses to critical structures in Auto-plans compared to Manual Plans across various clinical cases. Additionally, high gamma passing rates at 2%/2mm in both 2D (above 97%) and 3D (above 99%) in vivo analyses further validate the accuracy and reliability of treatment plans.

CONCLUSIONS: The DEIT platform represents a viable solution for radiation treatment. The DEIT system utilizes AI-driven automation, real-time adjustments, and CT imaging to enhance the radiotherapy process, improving both efficiency and flexibility.

PMID:39921109 | DOI:10.1016/j.ijrobp.2025.01.028

Respir Med. 2025 Feb 5:107986. doi: 10.1016/j.rmed.2025.107986. Online ahead of print.

ABSTRACT

BACKGROUND: Idiopathic pleuroparenchymal fibroelastosis (iPPFE) is a distinctive chronic interstitial lung disease characterized by upper lobe-dominant elastofibrosis. Deepening of the suprasternal notch is a notable physical feature in patients with iPPFE. However, the anatomical explanation and clinical significance of iPPFE have not yet been studied in detail.

METHODS: We retrospectively examined 84 patients with iPPFE, 59 with idiopathic pulmonary fibrosis (IPF), 32 with chronic hypersensitivity pneumonitis (CHP), and 91 non-interstitial lung disease (ILD) controls. The depth of the suprasternal notch assessed on axial chest computed tomography and its association with clinical, radiological, and physiological parameters, and patient outcomes were investigated.

RESULTS: The depth of the suprasternal notch was anatomically correlated with the thickness of the pre-tracheal soft tissue and posterior or right deviation of the trachea in patients with iPPFE. The depth of the suprasternal notch effectively discriminated patients with iPPFE from those with IPF (sensitivity, 75%; specificity, 86.4%), CHP (sensitivity, 75%; specificity, 84.4%), and non-ILD controls (sensitivity, 75%; specificity, 83.5%), with a cutoff value of 9.5 mm. A log-rank test showed that patients with iPPFE with a deep suprasternal notch had significantly shorter survival than those without a deep suprasternal notch. In addition, a multivariate Cox regression analysis adjusted for age, sex, and %forced vital capacity showed that the depth of the suprasternal notch was an independent risk factor for mortality.

CONCLUSION: The suprasternal notch is a simple and useful indicator with diagnostic and prognostic implications for patients with iPPFE.

PMID:39921067 | DOI:10.1016/j.rmed.2025.107986

Nucleic Acids Res. 2025 Feb 8;53(4):gkaf058. doi: 10.1093/nar/gkaf058.

ABSTRACT

Transcription factors (TFs) are often classified as activators or repressors, yet these context-dependent labels are inadequate to predict quantitative profiles that emerge across different promoters. A mechanistic understanding of how different regulatory sequences shape TF function is challenging due to the lack of systematic genetic control in endogenous genes. To address this, we use a library of Escherichia coli strains with precise control of TF copy number, measuring the quantitative regulatory input-output function of 90 TFs on synthetic promoters that isolate the contributions of TF binding sequence, location, and basal promoter strength to gene expression. We interpret the measured regulation of these TFs using a thermodynamic model of gene expression and uncover stabilization of RNA polymerase as a pervasive regulatory mechanism, common to both activating and repressing TFs. This property suggests ways to tune the dynamic range of gene expression through the interplay of stabilizing TF function and RNA polymerase basal occupancy, a phenomenon we confirm by measuring fold change for stabilizing TFs across synthetic promoter sequences spanning over 100-fold basal expression. Our work deconstructs TF function at a mechanistic level, providing foundational principles on how gene expression is realized across different promoter contexts, with implications for decoding the relationship between sequence and gene expression.

PMID:39921566 | DOI:10.1093/nar/gkaf058

Adv Sci (Weinh). 2025 Feb 8:e2411459. doi: 10.1002/advs.202411459. Online ahead of print.

ABSTRACT

Tailored droplet generation is crucial for droplet microfluidics that involve samples of varying sizes. However, the absence of precise predictive models forces droplet platforms to rely on empiricism derived from extensive experiments, underscoring the need for comprehensive modeling analysis. To address this, a novel customized assembled centrifugal step emulsifier (CASE) is presented by incorporating a "jigsaw puzzles" design to efficiently acquire large-scale experimental data. Numerical simulations are utilized to analyze fluid configurations during step emulsification, identifying a key connection tube that determines droplet size. By training and verifying with the experimental and simulation datasets, a comprehensive theoretical model is established that allows for the preliminary design of the droplet size and generation frequency with an average error rate of 4.8%, successfully filling a critical gap in existing field. This predictive model empowers the CASE to achieve all-in-one functionality, including droplet pre-design, generation, manipulation, and on-site detection. As a proof of concept, multiscale sample analysis ranging from nanoscale nucleic acids to microscale bacteria and 3D cell spheroids is realized in the CASE. In summary, this platform offers valuable guidance for customized droplet generation by centrifugal step emulsifiers and promotes the adoption of droplet microfluidics in biochemical assays.

PMID:39921431 | DOI:10.1002/advs.202411459

Adv Sci (Weinh). 2025 Feb 7:e2406021. doi: 10.1002/advs.202406021. Online ahead of print.

ABSTRACT

Re-epithelialization constitutes a critical stage in the intricate process of wound healing, yet its mechanisms in the context of diabetic wounds remain elusive. In this study, the role of the mesenchymal-epithelial transition (MET) vis-à-vis the epithelial-mesenchymal transition (EMT) of keratinocytes in diabetic wound re-epithelialization is investigated. The findings reveal an impediment in the MET process, rather than EMT, which significantly compromised re-epithelialization in diabetic wounds. Furthermore, Desmoplakin (DSP) gene expression, encoding a key desmosome protein, is down-regulated in diabetic rats. This down-regulation coincided with aberrant hypo-demethylation of the DSP promoter. The inhibition of DSP expression is linked to reduced occupancy of Ten-eleven translocation 3 (TET3) at the DSP promoter, consequently suppressing TET3-dependent DNA demethylation. Additionally, a novel lncRNA termed DSP-AS1is identified, which is antisense to DSP. Notably, DSP-AS1 expression is down-regulated in diabetic skin wounds, and it interacted with TET3, a DNA demethylase. Notably, DSP-AS1 is found to form R-loops, triple-stranded DNA:RNA hybrids, at the DSP promoter, facilitating TET3 localization to the DSP promoter. Collectively, the findings suggest that reduced R-loop formation by DSP-AS1 impairs DSP gene transcription by repressing TET3-mediated DNA demethylation. This disruption of the orchestrated re-epithelialization process contributes to refractory diabetic wound healing.

PMID:39921255 | DOI:10.1002/advs.202406021

Indian J Gastroenterol. 2025 Feb 8. doi: 10.1007/s12664-024-01720-0. Online ahead of print.

ABSTRACT

BACKGROUND: This systematic review and meta-analysis evaluated the incidence of serious adverse events (SAEs) in patients with Crohn's disease (CD) and ulcerative colitis (UC) treated with upadacitinib and examined secondary adverse events.

METHODS: A comprehensive search of PubMed, Embase and Cochrane Library was conducted to identify randomized controlled trials (RCTs) comparing upadacitinib with placebo in adults with inflammatory bowel disease (IBD). The primary outcome was the incidence of SAEs, while secondary outcomes included specific adverse events. Risk ratios (RR) with 95% confidence intervals (CI) were calculated.

RESULTS: Six RCTs, including 2611 patients, were analyzed. The incidence of SAEs did not significantly differ between upadacitinib (6.1%) and placebo (7%) (RR = 0.77; 95% CI: 0.50-1.20; p = 0.25). Secondary outcomes showed no significant differences in serious infections, hepatic disorders, nasopharyngitis or herpes zoster. However, neutropenia (RR = 5.63; 95% CI: 1.90-16.65; p = 0.0002) and creatine kinase elevation (RR = 2.34; 95% CI: 1.22-4.47; p = 0.01) were higher with upadacitinib, while anemia (RR = 0.36; 95% CI: 0.27-0.48; p < 0.00001) and arthralgia (RR = 0.47; 95% CI: 0.30-0.75; p = 0.001) were reduced.

CONCLUSION: Upadacitinib did not increase the overall risk of SAEs in IBD patients, with a notable reduction in anemia and arthralgia. However, the higher risks of neutropenia and CK elevation underscore the importance of monitoring. Further research is necessary to assess long-term safety, particularly regarding rare but serious events such as thromboembolism.

PMID:39921836 | DOI:10.1007/s12664-024-01720-0

J Thromb Haemost. 2025 Feb 5:S1538-7836(25)00050-9. doi: 10.1016/j.jtha.2025.01.008. Online ahead of print.

ABSTRACT

BACKGROUND: Andexanet alfa, a Food and Drug Administration (FDA)-approved antidote for apixaban and rivaroxaban, is used to manage life-threatening or uncontrolled bleeding. In patients undergoing cardiopulmonary bypass (CPB), prior exposure to andexanet can cause severe heparin resistance, necessitating effective mitigation strategies. A comprehensive review of such strategies remains lacking.

OBJECTIVE: To systematically review and characterize cases of andexanet-induced heparin resistance in patients undergoing CPB and to evaluate management strategies.

METHODS: A systematic search was conducted across multiple databases via the Ovid interface, Cochrane Central Register of Controlled Trials, and the FDA Adverse Event Reporting System. Quality appraisal was performed using a validated instrument for case reports and series describing drug-induced adverse events.

RESULTS: Fourteen discrete patient cases met inclusion criteria. Post-andexanet administration, the mean initial activated clotting time (ACT) was 199.5 seconds, falling short of a target of >400 seconds despite additional heparin dosing (mean total: 1,123 U/kg). 35.7% of all cases involved thrombus formation in the reservoir; two of which required a circuit replacement. Antithrombin (AT) concentrate was administered to 75% of those received an adjunct therapy. A prophylactic AT use (mean, 49.9 IU/kg) resulted in an ACT over 400 seconds, while its effects in low-dose after the occurrence of thrombosis varied on ACT values. Nafamostat mesylate was used in some cases reported from Japan CONCLUSIONS: Heparin resistance following andexanet exposure poses significant procoagulant risk during CPB. Preemptive high-dose antithrombin therapy may improve ACT values. Further studies are needed to understand the mechanisms and optimize management of this condition.

PMID:39920998 | DOI:10.1016/j.jtha.2025.01.008

BMC Pharmacol Toxicol. 2025 Feb 7;26(1):27. doi: 10.1186/s40360-025-00867-6.

ABSTRACT

OBJECTIVE: By using the FAERS database, we aim to identify and assess risk signals of adverse drug events (ADEs) potentially causing pericardial effusion, to inform clinical drug management and promote rational drug use.

METHODS: We obtained reports of pericardial effusion events from the FAERS database spanning from the first quarter of 2004 to the second quarter of 2024, and identified the top 50 drugs ranked by report frequency or signal strength. Four algorithms, namely the reported odds ratio (ROR), proportional reporting ratio (PRR), Bayesian confidence propagation neural network (BCPNN), and multi-item gamma Poisson shrinker (MGPS), were employed for signal detection of these drugs. Furthermore, for drugs with positive signals, we conducted sensitivity analyses and employed the Weibull shape parameter test to perform a time to onset (TTO) analysis.

RESULTS: We identified 20,057 ADEs related to pericardial effusion, involving 19,693 patients for analysis. The patient population comprised 10,187 males (51.7%) and 7,939 females (40.3%). Adults aged 18-65 years were the largest group (7,798 cases, 39.6%). Regarding clinical outcomes, 9,924 patients (50.4%) experienced hospitalization, and 2,770 cases (14.1%) resulted in death. Ranked by the ROR risk signal strength, the top 3 drugs were hydralazine [ROR (95% CI): 27.11 (22.28-33)], dasatinib [ROR (95% CI): 15.62 (14.07-17.33)], and mesalazine [ROR (95% CI): 8.99 (6.84-11.8)]. We conducted a TTO analysis for the 26 drugs with positive signals. The median TTO and interquartile range (IQR) for the top 3 drugs causing the earliest pericardial effusion were: cytarabine 14 (7.5,38), selexipag 14.5 (4.25, 157.75), dabigatran etexilate 29 (9, 229). Most drugs exhibited an early failure type.

CONCLUSION: This study systematically compiled a list of drugs with potential risks of causing pericardial effusion. There is a significant association between pericardial effusion and the use of hydralazine, dasatinib, and mesalazine. Moreover, pericardial effusion is more common in patient groups receiving treatments with antineoplastic and immunomodulating agents.

PMID:39920868 | DOI:10.1186/s40360-025-00867-6

BMC Med. 2025 Feb 7;23(1):76. doi: 10.1186/s12916-025-03919-0.

ABSTRACT

BACKGROUND: Fluoroquinolone antibiotics have a high potential for serious adverse drug reactions, but real-world evidence in European patient cohorts is lacking. Therefore, we aim to examine the association between fluoroquinolone exposure and potentially life-threatening adverse events stratified by age and gender in Germany.

METHODS: We conducted an administrative cohort study using the active comparator new user design with a risk window up to 365 days between January 2013 and December 2019. Population-based longitudinal data from one of the largest German statutory health insurances were used. Episodes of newly dispensed fluoroquinolones (ciprofloxacin, levofloxacin, ofloxacin, moxifloxacin, norfloxacin, and enoxacin) were compared to other antibiotics (amoxicillin, amoxicillin clavulanic acid, azithromycin, cefuroxime, cephalexin, clindamycin, sulfamethoxazole-trimethoprim, and doxycycline). Endpoints were defined by incident diagnoses of aortic aneurysm/dissection, cardiac arrhythmia, hepatotoxicity, and all-cause mortality. Adjusted hazard ratios were estimated from piece-wise exponential additive mixed models with smooth non-linear effects for person-time and age and adjusted for comorbidities, year and quarter at index.

RESULTS: The cohorts comprised 15,139,840; 11,760,159; 11,027,175; and 15,305,757 antibiotic episodes. Patients during fluoroquinolone episodes were older (59 versus 51 years) and more often female (58% versus 54%). We counted 46,502; 446,727; 19,125; and 474,411 incident endpoints. Relative risk for all-cause mortality and hepatotoxicity was high for < 40-year- and 40-69-year-old females (aHR = 1.77, 95% CI 1.55-2.03 and aHR = 1.42, 95% CI 1.32-1.53), respectively. For aortic aneurysm/dissection a nominally increased relative risk for < 40-year-old females was found (aHR = 1.42, 95% CI 0.96-2.11), although 95% CI indicates that a small relative risk reduction is also supported by the data. Relative risk for cardiac arrhythmia was increased for men aged < 40 years (aHR = 1.14, 95% CI 1.08-1.20). High relative risks for each endpoint were also identified depending on choice of active comparator, and risks increased with higher defined daily doses and shorter follow-up.

CONCLUSIONS: This study contributes real-world evidence to endpoint-specific differences of risks in patient subgroups which need to be considered to improve fluoroquinolone drug safety.

PMID:39920723 | DOI:10.1186/s12916-025-03919-0

BMC Cancer. 2025 Feb 7;25(1):216. doi: 10.1186/s12885-025-13614-1.

ABSTRACT

BACKGROUND: Immune checkpoint inhibitor (ICI) therapy is increasingly used to treat non-small cell lung cancer (NSCLC). However, little attention has been given to the comparative analysis of adverse events (AEs) associated with different ICIs.

METHODS: Disproportionality analysis and Bayesian confidence propagation neural network (BCPNN) were utilized to identify pharmacovigilance signals from the FDA Adverse Event Reporting System (FAERS). We compared the sex distribution of patients, risk of suffering more severe adverse reactions, and risk of hospitalization associated with different ICIs, using pairwise matrices that displayed odds ratio (OR) and their 95% confidence interval (CI). And we also compared the outcomes of reactions by using ordinal logistic regression.

RESULTS: We analyzed 13,580 reports of AEs associated with five ICIs, namely, durvalumab, pembrolizumab, ipilimumab, atezolizumab, and nivolumab from January 2013 to October 2022. Significant differences were observed in sex distribution of patients, risk of suffering more severe adverse reactions, risk of hospitalization, and the outcomes of reactions. In terms of respiratory AEs, pembrolizumab exhibited a higher risk compared to durvalumab (OR = 2.48, 95% CI: 1.72-3.59), atezolizumab (OR = 1.84, 95% CI: 1.07-3.16), and nivolumab (OR = 4.21, 95% CI: 1.72-10.28), while ipilimumab exhibited a higher risk compared to durvalumab (OR = 2.76, 95% CI: 1.14-6.65) and nivolumab (OR = 4.67, 95% CI: 1.14-15.51). In terms of endocrine and metabolic AEs, durvalumab (OR = 7.80, 95% CI: 1.33-45.90) and nivolumab (OR = 5.20, 95% CI: 1.17-23.03) exhibited a higher risk compared to ipilimumab.

CONCLUSION: Each ICI has distinctive features of pharmacovigilance signals. It is essential to acknowledge the AEs associated with the relevant system when clinicians administer ICIs.

PMID:39920614 | DOI:10.1186/s12885-025-13614-1

Sci Rep. 2025 Feb 7;15(1):4641. doi: 10.1038/s41598-024-84737-x.

ABSTRACT

Dental caries is a very common chronic disease that may lead to pain, infection, and tooth loss if its diagnosis at an early stage remains undetected. Traditional methods of tactile-visual examination and bitewing radiography, are subject to intrinsic variability due to factors such as examiner experience and image quality. This variability can result in inconsistent diagnoses. Thus, the present study aimed to develop a deep learning-based AI model using the YOLOv8 algorithm for improving interproximal caries detection in bitewing radiographs. In this retrospective study on 552 radiographs, a total of 1,506 images annotated at Tehran University of Medical Science were processed. The YOLOv8 model was trained and the results were evaluated in terms of precision, recall, and the F1 score, whereby it resulted in a precision of 96.03% for enamel caries and 80.06% for dentin caries, thus showing an overall precision of 84.83%, a recall of 79.77%, and an F1 score of 82.22%. This proves its reliability in reducing false negatives and improving diagnostic accuracy. YOLOv8 enhances interproximal caries detection, offering a reliable tool for dental professionals to improve diagnostic accuracy and clinical outcomes.

PMID:39920198 | DOI:10.1038/s41598-024-84737-x

Sci Rep. 2025 Feb 8;15(1):4693. doi: 10.1038/s41598-024-83721-9.

ABSTRACT

Complete and high-quality photodocumentation in esophagoduodenogastroscopy (EGD) is essential for accurately diagnosing upper gastrointestinal diseases by reducing blind spot rates. Automated Photodocumentation Task (APT), an artificial intelligence-based system for real-time photodocumentation during EGD, was developed to assist endoscopists in focusing more on the observation rather than repetitive capturing tasks. This study aimed to evaluate the completeness and quality of APT's photodocumentation compared to endoscopists. The dataset comprised 37 EGD videos recorded at Seoul National University Hospital between March and June 2023. Virtual endoscopy was conducted by seven endoscopists and APT, capturing 11 anatomical landmarks from the videos. The primary endpoints were the completeness of capturing landmarks and the quality of the images. APT achieved an average accuracy of 98.16% in capturing landmarks. Compared to that of endoscopists, APT demonstrated similar completeness in photodocumentation (87.72% vs. 85.75%, P = .0.258), and the combined photodocumentation of endoscopists and APT reached higher completeness (91.89% vs. 85.75%, P < .0.001). APT captured images with higher mean opinion scores than those of endoscopists (3.88 vs. 3.41, P < .0.001). In conclusion, APT provides clear, high-quality endoscopic images while minimizing blind spots during EGD in real-time.

PMID:39920187 | DOI:10.1038/s41598-024-83721-9

Sci Rep. 2025 Feb 7;15(1):4633. doi: 10.1038/s41598-024-82241-w.

ABSTRACT

Accurately and early diagnosis of melanoma is one of the challenging tasks due to its unique characteristics and different shapes of skin lesions. So, in order to solve this issue, the current study examines various deep learning-based approaches and provide an effective approach for classifying dermoscopic images into two categories of skin lesions. This research focus on skin cancer images and provides solution using deep learning approaches. This research investigates three approaches for classifying skin cancer images. (1) Utilizing three fine-tuned pre-trained networks (VGG19, ResNet18, and MobileNet_V2) as classifiers. (2) Employing three pre-trained networks (ResNet-18, VGG19, and MobileNet v2) as feature extractors in conjunction with four machine learning classifiers (SVM, DT, Naïve Bayes, and KNN). (3) Utilizing a combination of the aforementioned pre-trained networks as feature extractors in conjunction with same machine learning classifiers. All these algorithms are trained using segmented images which are achieved by using the active contour approach. Prior to segmentation, preprocessing step is performed which involves scaling, denoising, and enhancing the image. Experimental performance is measured on the ISIC 2018 dataset which contains 3300 images of skin disease including benign and malignant type cancer images. 80% of the images from the ISIC 2018 dataset are allocated for training, while the remaining 20% are designated for testing. All approaches are trained using different parameters like epoch, batch size, and learning rate. The results indicate that combining ResNet-18 and MobileNet pre-trained networks using concatenation with an SVM classifier achieved the maximum accuracy of 92.87%.

PMID:39920179 | DOI:10.1038/s41598-024-82241-w

Sci Rep. 2025 Feb 7;15(1):4576. doi: 10.1038/s41598-025-88477-4.

ABSTRACT

Autoimmune Diseases are a complex group of diseases caused by the immune system mistakenly attacking body tissues. Their etiology involves multiple factors such as genetics, environmental factors, and abnormalities in immune cells, making prediction and treatment challenging. T cells, as a core component of the immune system, play a critical role in the human immune system and have a significant impact on the pathogenesis of autoimmune diseases. Several studies have demonstrated that T-cell receptors (TCRs) may be involved in the pathogenesis of various autoimmune diseases, which provides strong theoretical support and new therapeutic targets for the prediction and treatment of autoimmune diseases. This study focuses on the prediction of several autoimmune diseases mediated by T cells, and proposes two models: one is the AutoY model based on convolutional neural networks, and the other is the LSTMY model, a bidirectional LSTM network model that integrates the attention mechanism. Experimental results show that both models exhibit good performance in the prediction of the four autoimmune diseases, with the AutoY model performing slightly better in comparison. In particular, the average area under the ROC curve (AUC) of the AutoY model exceeded 0.93 in the prediction of all the diseases, and the AUC value reached 0.99 in two diseases, type 1 diabetes and multiple sclerosis. These results demonstrate the high accuracy, stability, and good generalization ability of the two models, which makes them promising tools in the field of autoimmune disease prediction and provides support for the use of the TCR bank for the noninvasive detection of autoimmune disease non-invasive detection is supported.

PMID:39920178 | DOI:10.1038/s41598-025-88477-4

Sci Rep. 2025 Feb 7;15(1):4662. doi: 10.1038/s41598-025-86727-z.

ABSTRACT

The objective was to use convolutional neural networks (CNNs) for automatic segmentation of hip cartilage and labrum based on 3D MRI. In this retrospective single-center study, CNNs with a U-Net architecture were used to develop a fully automated segmentation model for hip cartilage and labrum from MRI. Direct hip MR arthrographies (01/2020-10/2021) were selected from 100 symptomatic patients. Institutional routine protocol included a 3D T1 mapping sequence, which was used for manual segmentation of hip cartilage and labrum. 80 hips were used for training and the remaining 20 for testing. Model performance was assessed with six evaluation metrics including Dice similarity coefficient (DSC). In addition, model performance was tested on an external dataset (40 patients) with a 3D T2-weighted sequence from a different institution. Inter-rater agreement of manual segmentation served as benchmark for automatic segmentation performance. 100 patients were included (mean age 30 ± 10 years, 64% female patients). Mean DSC for cartilage was 0.92 ± 0.02 (95% confidence interval [CI] 0.92-0.93) and 0.83 ± 0.04 (0.81-0.85) for labrum and comparable (p = 0.232 and 0.297, respectively) to inter-rater agreement of manual segmentation: DSC cartilage 0.93 ± 0.04 (0.92-0.95); DSC labrum 0.82 ± 0.05 (0.80-0.85). When tested on the external dataset, the DSC was 0.89 ± 0.02 (0.88-0.90) and 0.71 ± 0.04 (0.69-0.73) for cartilage and labrum, respectively.The presented deep learning approach accurately segments hip cartilage and labrum from 3D MRI sequences and can potentially be used in clinical practice to provide rapid and accurate 3D MRI models.

PMID:39920175 | DOI:10.1038/s41598-025-86727-z

Hum Genomics. 2025 Feb 7;19(1):11. doi: 10.1186/s40246-025-00720-1.

ABSTRACT

Pharmacogenomics (PGx) aims to delineate a patient's genetic profile with differences in drug efficacy and/or toxicity, particularly focusing on genes encoding for drug-metabolizing enzymes and transporters. Clinical implementation of PGx is a complex undertaking involving a multidisciplinary approach that includes, among others, a thorough understanding of a country's preparedness to adopt this modern discipline and a detailed knowledge of PGx biomarkers allelic spectrum at a population level. In several European populations, particularly in countries with lower income, clinical implementation of PGx is still in its infancy. We have previously performed a pilot study to determine the prevalence of PGx biomarkers in 18 European populations, as the first step towards population PGx at the European level. Here, we provide a comprehensive analysis of the current state of PGx in Greece, including a detailed allelic frequency spectrum of clinically actionable PGx biomarkers, the level of PGx education in academia, the provision of PGx testing services from public and private laboratories, and the aspects of the regulatory PGx environment, especially with respect to the discrepancies between the Greek National Organization of Medicines and the European Medicine Agency and health technology assessment. This study would not only provide the foundations for expediting the adoption of PGx in clinical reality in Greece but can also serve as a paradigm for replicating future studies in other European countries, to expand on previously available pilot studies.

PMID:39920803 | DOI:10.1186/s40246-025-00720-1

J Cyst Fibros. 2025 Feb 6:S1569-1993(25)00046-3. doi: 10.1016/j.jcf.2025.01.013. Online ahead of print.

ABSTRACT

BACKGROUND: Pulmonary infections with multidrug-resistant nontuberculous mycobacteria (NTM), particularly Mycobacterium abscessus (MAB), are increasingly more prevalent in individuals with lung disease such as cystic fibrosis and are extremely difficult to treat. Protracted antibiotic therapies consist of multidrug regimens that last for months to years. Despite these intense protocols, failure rates are high with 50%-60% of patients not achieving a sustained culture-negative status. A major contributor to the difficult medical management of NTM infections is formation of pulmonary aggregate MAB biofilms which protect the resident bacteria from antimicrobials and host immune effectors. Thereby, novel and more effective approaches to combat recalcitrant NTM infections are urgently needed.

METHODS: We developed an epitope-targeted monoclonal antibody-based technology to rapidly disrupt biofilms and release resident bacteria into a transient yet highly vulnerable phenotype that is significantly more sensitive to killing by both antibiotics and host innate immune effectors (e.g., PMNs and antimicrobial peptides). Herein, we tested this technology in a pre-clinical murine lung infection model to determine whether this treatment would mediate clearance of MAB from the lungs and speed return to homeostasis.

RESULTS: As early as 48 h after a single treatment, bacterial loads were reduced to below the level of detection and histopathologic analysis showed markedly decreased inflammation and rapid eradication of aggregate biofilms compared to controls.

CONCLUSIONS: These new data add to those from multiple prior published studies which show the significant efficacy of this novel therapeutic approach to resolve recalcitrant bacterial biofilm diseases, now potentially including those induced by NTM.

PMID:39919951 | DOI:10.1016/j.jcf.2025.01.013

J Cyst Fibros. 2025 Feb 6:S1569-1993(25)00048-7. doi: 10.1016/j.jcf.2025.01.015. Online ahead of print.

ABSTRACT

BACKGROUND: Elucidating the molecular and cellular effects caused by CFTR variants is crucial to understand Cystic Fibrosis (CF) disease pathophysiology, but also to predict disease severity, to provide genetic counselling, and to determine the most adequate therapeutic strategy for people with CF (pwCF). While the current CFTR modulator drugs (CFTRm) are approved mainly for pwCF with the most prevalent variant, p.Phe508del, pwCF carrying rare and/or uncharacterized CFTR variants are not eligible. However, previous studies have shown that such rare variants can be rescued by the approved CFTRm, suggesting clinical benefit for those pwCF. Here, we characterized the rare and non-eligible p.Ile148Asn CFTR variant found in Portuguese pwCF, regarding CFTR processing, traffic and function, and response to existing CFTRm.

METHODS: We used the forskolin-induced swelling (FIS) assay in intestinal organoids (IOs) from 2 CF individuals carrying p.Ile148Asn in heterozygosity with p.Phe508del and p.Gly542Ter, respectively. Additionally, a Cystic Fibrosis Bronchial Epithelial (CFBE) cell line expressing p.Ile148Asn-CFTR was generated to study the molecular defect of this variant individually.

RESULTS: Our results show that p.Ile148Asn is a CF-causing variant, impairing both CFTR plasma membrane (PM) traffic and function, albeit partially. Moreover, p.Ile148Asn-CFTR can be rescued by approved CFTRm in CFBE cells and IOs, suggesting potential clinical benefit for these individuals.

CONCLUSION: The work emphasizes the importance of testing CFTRm for rare variants not included in the drug label. It also shows that the 'theranostic' approach using IOs from pwCF, which captures the genetic background of each individual, complements theratyping in cell lines that focuses only on CFTR variants.

PMID:39919950 | DOI:10.1016/j.jcf.2025.01.015

Dev Cell. 2025 Feb 4:S1534-5807(25)00031-0. doi: 10.1016/j.devcel.2025.01.011. Online ahead of print.

ABSTRACT

Cellular stresses, particularly endoplasmic reticulum (ER) stress induced by ER-to-Golgi transport blockade, trigger Golgi-independent secretion of cytosolic and transmembrane proteins. However, the molecular mechanisms underlying this unconventional protein secretion (UPS) remain largely elusive. Here, we report that an ER tubulovesicular structure (ER tubular body [ER-TB]), shaped by the tubular ER-phagy receptors ATL3 and RTN3L, plays an important role in stress-induced UPS of transmembrane proteins such as cystic fibrosis transmembrane conductance regulator (CFTR) and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike protein. Correlative light-electron microscopy analyses demonstrate the formation of ER-TB under UPS-inducing conditions in HEK293 and HeLa cells. Individual gene knockdowns of ATL3 and RTN3 inhibit ER-TB formation and the UPS of trafficking-deficient ΔF508-CFTR. Combined supplementation of ATL3 and RTN3L induces ER-TB formation and UPS. ATL3 also participates in the SARS-CoV-2-associated convoluted membrane formation and Golgi-independent trafficking of SARS-CoV-2 spike protein. These findings suggest that ER-TB serves a common function in mediating stress-induced UPS, which participates in various physiological and pathophysiological processes.

PMID:39919755 | DOI:10.1016/j.devcel.2025.01.011