Front Oncol. 2025 Feb 25;15:1491843. doi: 10.3389/fonc.2025.1491843. eCollection 2025.

ABSTRACT

PURPOSE: This study aims to investigate the diagnostic accuracy of various deep learning methods on DCE-MRI, in order to provide a simple and accessible tool for predicting pathologic response of NAC in breast cancer patients.

METHODS: In this study, we enrolled 313 breast cancer patients who had complete DCE-MRI data and underwent NAC followed by breast surgery. According to Miller-Payne criteria, the efficacy of NAC was categorized into two groups: the patients achieved grade 1-3 of Miller-Payne criteria were classified as the non-responders, while patients achieved grade 4-5 of Miller-Payne criteria were classified as responders. Multiple deep learning frameworks, including ViT, VGG16, ShuffleNet_v2, ResNet18, MobileNet_v2, MnasNet-0.5, GoogleNet, DenseNet121, and AlexNet, were used for transfer learning of the classification model. The deep learning features were obtained from the final fully connected layer of the deep learning models, with 256 features extracted based on DCE-MRI data for each patient of each deep learning model. Various machine-learning techniques, including support vector machine (SVM), K-nearest neighbor (KNN), RandomForest, ExtraTrees, XGBoost, LightGBM, and multiple-layer perceptron (MLP), were employed to construct classification models.

RESULTS: We utilized various deep learning models to extract features and subsequently constructed machine learning models. Based on the performance of different machine learning models' AUC values, we selected the classifiers with the best performance. ResNet18 exhibited superior performance, with an AUC of 0.87 (95% CI: 0.82 - 0.91) and 0.87 (95% CI: 0.78 - 0.96) in the train and test cohorts, respectively.

CONCLUSIONS: Using pre-treatment DCE-MRI images, our study trained multiple deep models and developed the best-performing DLR model for predicting pathologic response of NAC in breast cancer patients. This prognostic tool provides a dependable and impartial basis for effectively identifying breast cancer patients who are most likely to benefit from NAC before its initiation. At the same time, it can also identify those patients who are insensitive to NAC, allowing them to proceed directly to surgical treatment and prevent the risk of losing the opportunity for surgery due to disease progression after NAC.

PMID:40071096 | PMC:PMC11893424 | DOI:10.3389/fonc.2025.1491843

Front Oncol. 2025 Feb 25;15:1499223. doi: 10.3389/fonc.2025.1499223. eCollection 2025.

ABSTRACT

Colorectal cancer (CRC) is a prevalent malignant tumor in the digestive system. As reported in the 2020 global cancer statistics, CRC accounted for more than 1.9 million new cases and 935,000 deaths, making it the third most common cancer worldwide in terms of incidence and the second leading cause of cancer-related deaths globally. This poses a significant threat to global public health. Early screening methods, such as fecal occult blood tests, colonoscopies, and imaging techniques, are crucial for detecting early lesions and enabling timely intervention before cancer becomes invasive. Early detection greatly enhances treatment possibilities, such as surgery, radiation therapy, and chemotherapy, with surgery being the main approach for treating early-stage CRC. In this context, artificial intelligence (AI) has shown immense potential in revolutionizing CRC management, serving as one of the most effective screening tools. AI, utilizing machine learning (ML) and deep learning (DL) algorithms, improves early detection, diagnosis, and treatment by processing large volumes of medical data, uncovering hidden patterns, and forecasting disease development. DL, a more advanced form of ML, simulates the brain's processing power, enhancing the accuracy of tumor detection, differentiation, and prognosis predictions. These innovations offer the potential to revolutionize cancer care by boosting diagnostic accuracy, refining treatment approaches, and ultimately enhancing patient outcomes.

PMID:40071094 | PMC:PMC11893421 | DOI:10.3389/fonc.2025.1499223

HCA Healthc J Med. 2025 Feb 1;6(1):11-21. doi: 10.36518/2689-0216.1802. eCollection 2025.

ABSTRACT

Description Idiopathic pulmonary fibrosis (IPF) is a progressive disease characterized by gradual destruction and replacement of pulmonary parenchyma with fibrous tissue, which occurs in conjunction with chronic inflammation. It is often considered a prototypical interstitial lung disease and is both the most prevalent and perhaps the most dangerous in that family. Although the disease is uncommon in the general population, its prevalence increases with age and is typically diagnosed around the age of 65. This does not preclude the development of IPF in younger individuals, and the mean survival is 2 to 5 years post-diagnosis regardless of age. Contemporary studies have provided insight into how altered pulmonary parenchyma results in increased susceptibility to opportunistic infections. It has also been demonstrated that pulmonary insults that cause inflammation, such as pneumonia, may accelerate the progression of IPF. Eosinophilic pneumonias are a collection of pulmonary diseases in which eosinophil-mediated inflammation results in respiratory compromise. Early recognition and appropriate intervention are imperative to minimize the risk of residual pulmonary function deficits, a risk that is increased in individuals with separate pulmonary risk factors. While prompt diagnosis and pharmacologic interventions are associated with improved outcomes, patients with IPF remain at risk of deterioration to the point of requiring lung transplantation. Early screening for those at risk continues to be a topic of interest. Despite the prevalence of IPF, its pathogenesis remains poorly understood and few management options are available. In this article, we document a unique case of previously undiagnosed IPF in a young individual that acutely worsened in the setting of acute eosinophilic pneumonia and the involvement of an opportunistic organism, Aspergillus niger. The case section will serve as a transition into a discussion of each of the major pathologic factors at play, supported by a review of recent literature.

PMID:40071189 | PMC:PMC11892399 | DOI:10.36518/2689-0216.1802

Clin Respir J. 2025 Mar;19(3):e70061. doi: 10.1111/crj.70061.

ABSTRACT

INTRODUCTION: Anti-neutrophil cytoplasmic antibody (ANCA) seropositivity strongly correlates to ANCA-associated vasculitis. Patients with idiopathic interstitial pneumonias (IIPs) without systemic vasculitis are sometimes ANCA-positive. Radiological and pathological differences between patients with myeloperoxidase (MPO)-ANCA-positive and those with proteinase 3 (PR3)-ANCA-positive IIPs remain unclear. To determine whether high-resolution computed tomography (HRCT) features and pathology findings differ by ANCA subtype in ANCA-positive IIP patients in a national database. Clinical, radiological, and pathological data were examined along with a web-based multidisciplinary discussion.

METHODS: We reviewed records of 10 MPO-ANCA-positive and 9 PR3-ANCA-positive IIP patients who underwent HRCT and surgical lung biopsy between April 2009 and March 2014. Pulmonologists, chest radiologists, and pathologists evaluated HRCT scans and pathological findings independently. Patterns were classified using ATS/ERS/JRS/ALAT 2011 guidelines for idiopathic pulmonary fibrosis.

RESULTS: HRCT patterns were definite usual interstitial pneumonia (UIP) (n = 8; 42.1%), possible UIP (n = 6; 31.6%), and inconsistent with UIP (n = 5; 26.3%). Pathological patterns were definite UIP (n = 5; 26.3%), probable UIP (n = 8; 42.1%), possible UIP (n = 4; 21.1%), and not UIP (n = 2; 10.5%). HRCT and pathological patterns did not differ between MPO-ANCA-positive and PR3-ANCA-positive IIPs. Radiological features were reticulation (n = 13; 68.4%), nodules (n = 12; 63.1%), honeycombing (n = 10; 52.6%), and increased attenuation around honeycombing (n = 7; 36.8%). Pathological findings were cysts (n = 12; 63.1%), lymphoid follicles with germinal centers (n = 11; 57.9%), and peribronchiolar wall lymphocytic infiltration (n = 11; 57.9%).

CONCLUSION: HRCT and pathological patterns did not differ between MPO-ANCA-positive and PR3-ANCA-positive IIPs. This absence of significant differences suggests a similar mechanism underlying both types of interstitial pneumonia.

PMID:40070290 | DOI:10.1111/crj.70061

Biol Chem. 2025 Mar 13. doi: 10.1515/hsz-2025-0101. Online ahead of print.

ABSTRACT

The disruption of protein homeostasis leads to the increased un- and misfolding of proteins and the formation of toxic protein aggregates. Their accumulation triggers an unfolded protein response that is characterized by the transcriptional upregulation of molecular chaperones and proteases, and aims to restore proteome integrity, maintain cellular function, suppress the cause of perturbation, and prevent disease and death. In the green microalga Chlamydomonas reinhardtii, the study of this response to proteotoxic stress has provided insights into the function of chaperone and protease systems, which are, though simpler, closely related to those found in land plants. In addition, there has been considerable progress in understanding the triggers and regulation of compartment-specific unfolded protein responses. This review provides an overview on how the dysfunction of protein homeostasis is sensed in the different compartments of Chlamydomonas, and summarizes the current knowledge on the pathways that are triggered to restore equilibrium in the cell, while also highlighting similarities and differences to the unfolded protein responses of other model organisms.

PMID:40072221 | DOI:10.1515/hsz-2025-0101

Scand J Med Sci Sports. 2025 Mar;35(3):e70034. doi: 10.1111/sms.70034.

ABSTRACT

High cardiorespiratory fitness (CRF) is associated with better overall health. This study aimed to find a metabolic signature associated with CRF to identify health-promoting effects. CRF based on cardiopulmonary exercise testing, targeted and untargeted metabolomics approaches based on mass spectrometry, and clinical data from two independent cohorts of the Study of Health in Pomerania (SHIP) were used. Sex-stratified linear regression models were adjusted for age, smoking, and height to relate CRF with individual metabolites. A total of 132 (SHIP-START-2: 483 men with a median age of 58 years and 450 women with a median age of 56 years) and 118 (SHIP-TREND-0: 341 men and 371 women both with a median age of 51 years) metabolites were associated with CRF. Lipids showed bidirectional relations to CRF independent of sex. Specific subsets of sphingomyelins were positively related to CRF in men (SM (OH) C14:1, SM(OH)C22:2 SM C16:0, SM C20:2 SM(OH)C24:1) and inversely in women (SM C16:1, SM C18:0, SM C18:1). Metabolites involved in energy production (citrate and succinylcarnitine) were only associated with CRF in men. In women, xenobiotics (hippurate, stachydrine) were related to CRF. The sex-specific metabolic signature of CRF is influenced by sphingomyelins, energy substrates, and xenobiotics. The greater effect estimates seen in women may emphasize the important role of CRF in maintaining metabolic health. Future research should explore how this profile changes with different types of exercise interventions or diseases in diverse populations and how these metabolites could be implemented in primary prevention settings.

PMID:40072034 | DOI:10.1111/sms.70034

J Exp Bot. 2025 Mar 12:eraf116. doi: 10.1093/jxb/eraf116. Online ahead of print.

ABSTRACT

Plant metabolism is profoundly affected by various abiotic stresses. Consequently, plants must reconfigure their metabolic networks to sustain homeostasis while synthesizing compounds that mitigate stress. This aspect, with the current intensified climate impact results in more frequent abiotic stresses on a global scale. Advances in metabolomics and systems biology in the last decades have enabled both a comprehensive overview and a detailed analysis of key components involved in the plant metabolic response to abiotic stresses. This review addresses metabolic responses to altered atmospheric CO2 and O3, water deficit, temperature extremes, light intensity fluctuations including the importance of UV-B, ionic imbalance, and oxidative stress predicted to be caused by climate change, long-term shifts in temperatures and weather patterns. It also assesses both the commonalities and specificities of metabolic responses to diverse abiotic stresses, drawing on data from the literature. Classical stress-related metabolites such as proline, and polyamines are revisited, with an emphasis on the critical role of branched-chain amino acid metabolism under stress conditions. Finally, where possible, mechanistic insights into the regulation of metabolic processes and further outlook on combinatory stresses are discussed.

PMID:40071778 | DOI:10.1093/jxb/eraf116

Rheumatology (Oxford). 2025 Mar 1;64(Supplement_1):i38-i41. doi: 10.1093/rheumatology/keae556.

ABSTRACT

Spatial transcriptomics enables the study of the mechanisms of disease through gene expression and pathway activity analysis in a spatial context. Originally mainly employed in oncology, the techniques developed use different methods of transcript identification, resolution (single cells vs regions), flexibility of target regions and the type of molecules that can be assessed (RNA and/or protein). Selection of regions of interest requires both knowledge of the underlying histopathological changes and limitations of the methods, like artefacts due to variation in pre-analytics, or the probes used to analyse them. Here we review techniques currently available, their opportunities and limitations and discuss results obtained using Digital Spatial Profiling in pauci-immune focal necrotizing (and crescentic) glomerulonephritis (piFNGN) and giant cells arteritis (GCA). Spatial profiling techniques are powerful tools to investigate defined regions of interest in autoimmune and inflammatory disorders and allow for the identification of genes differentially expressed between different types of lesions and different disease aetiologies. Spatial profiling provides an example of a powerful methodology to investigate disease pathways in tissue at a local level across a spectrum of human diseases and generates hypotheses about molecular mechanisms that can be further investigated in detail. When implemented in the setting of a systems biology approach it may ultimately reach the goal of predicting the course of disease from histopathological slides.

PMID:40071426 | DOI:10.1093/rheumatology/keae556

iScience. 2025 Feb 11;28(3):111994. doi: 10.1016/j.isci.2025.111994. eCollection 2025 Mar 21.

ABSTRACT

Brain endothelial cells (BECs) play an important role in maintaining central nervous system (CNS) homeostasis through blood-brain barrier (BBB) functions. BECs express low baseline levels of adhesion receptors, which limits entry of leukocytes. However, the molecular mediators governing this phenotype remain mostly unclear. Here, we explored how infiltration of immune cells across the BBB is influenced by the scaffold protein IQ motif containing GTPase-activating protein 2 (IQGAP2). In mice and zebrafish, we demonstrate that loss of Iqgap2 increases infiltration of peripheral leukocytes into the CNS under homeostatic and inflammatory conditions. Using single-cell RNA sequencing and immunohistology, we further show that BECs from mice lacking Iqgap2 exhibit a profound inflammatory signature, including extensive upregulation of adhesion receptors and antigen-processing machinery. Human tissue analyses also reveal that Alzheimer's disease is associated with reduced hippocampal IQGAP2. Overall, our results implicate IQGAP2 as an essential regulator of BBB immune privilege and immune cell entry into the CNS.

PMID:40071147 | PMC:PMC11894336 | DOI:10.1016/j.isci.2025.111994

QRB Discov. 2025 Feb 18;6:e11. doi: 10.1017/qrd.2025.1. eCollection 2025.

ABSTRACT

Metabolism is at the core of all functions of living cells as it provides Gibbs free energy and building blocks for synthesis of macromolecules, which are necessary for structures, growth, and proliferation. Metabolism is a complex network composed of thousands of reactions catalyzed by enzymes involving many co-factors and metabolites. Traditionally it has been difficult to study metabolism as a whole network and most traditional efforts were therefore focused on specific metabolic pathways, enzymes, and metabolites. By using engineering principles of mathematical modeling to analyze and study metabolism, as well as engineer it, that is, design and build, new metabolic features, it is possible to gain many new fundamental insights as well as applications in biotechnology. Here, we present the history and basic principles of engineering metabolism, as well as the newest developments in the field. We are using examples of applications in: (1) production of protein pharmaceuticals and chemicals; (2) basic studies of metabolism; and (3) impacting health care. We will end by discussing how engineering metabolism can benefit from advances in artificial intelligence (AI)-based models.

PMID:40070847 | PMC:PMC11894412 | DOI:10.1017/qrd.2025.1

Front Immunol. 2025 Feb 25;16:1494624. doi: 10.3389/fimmu.2025.1494624. eCollection 2025.

ABSTRACT

Antigen specific humoral immunity can be characterized by the analysis of serum antibodies. While serological assays for the measurement of specific antibody levels are available, these are not quantitative in the biochemical sense. Yet, understanding humoral immune responses quantitatively on the systemic level would need a universal, complete, quantitative, comparable measurement method of antigen specific serum antibodies of selected immunoglobulin classes. Here we describe a fluorescent, dual-titration immunoassay, which provides the biochemical parameters that are both necessary and sufficient to quantitatively characterize the humoral immune response. For validation of theory, we used recombinant receptor binding domain of SARS-CoV-2 as antigen on microspot arrays and varied the concentration of both the antigen and the serum antibodies from infected persons to obtain a measurement matrix of binding data. Both titration curves were simultaneously fitted using an algorithm based on the generalized logistic function and adapted for analyzing biochemical variables of binding. We obtained equilibrium affinity constants and concentrations for distinct antibody classes. These variables reflect the quality and the effective quantity of serum antibodies, respectively. The proposed fluorescent dual-titration microspot immunoassay can generate truly quantitative serological data that is suitable for immunological, medical and systems biological analysis.

PMID:40070838 | PMC:PMC11893856 | DOI:10.3389/fimmu.2025.1494624

Sci Rep. 2025 Mar 11;15(1):8394. doi: 10.1038/s41598-025-92618-0.

ABSTRACT

Gut dysbiosis plays an important role in cirrhosis, but the mechanism of its development was not established. The aim of the study was to test the hypothesis that portal hypertension can be the main factor in the development of gut dysbiosis in cirrhosis. This cross-sectional study included 25 patients with chronic non-cirrhotic portal hypertension due to extrahepatic portal vein obstruction after portal vein thrombosis (PVT) (NCPVT group), 29 cirrhotic patients without PVT (CirNoPVT), 15 cirrhotic patients with chronic PVT (CPVT), and 22 healthy controls. The fecal microbiota was assessed using 16S rRNA gene sequencing. The CirNoPVT and CPVT groups had largely similar differences in gut microbiota composition from the control group. Patients with NCPVT, as well as patients with cirrhosis, had a higher abundance of Streptococcus, Escherichia, Enterococcus, Enterobacteriaceae, Enterococcaceae, Streptococcaceae, Bacilli, Gammaproteobacteria, Proteobacteria, and a lower abundance of Roseburia, Faecalibacterium, Methanobrevibacter, Ruminococcaceae, Methanobacteriaceae, Clostridia, Methanobacteria, and Euryarchaeota as they were compared with healthy individuals. Patients with NCPVT had a higher abundance of Bifidobacterium, Bifidobacteriaceae, Actinobacteria, and a lower abundance of Gemmiger and Catenibacterium compared to healthy individuals, which was not observed in the cirrhosis groups. The abundance of Porphyromonadaceae with the genus Parabacteroides was reduced in both groups with PVT, but not in CirNoPVT. There were no significant differences in gut microbiota beta-diversity among the CirNoPVT, CPVT and NCPVT groups. All these groups had significant differences in beta-diversity from the control group. Portal hypertension seems be the main factor in the development of gut dysbiosis in cirrhosis.

PMID:40069378 | DOI:10.1038/s41598-025-92618-0

Nat Struct Mol Biol. 2025 Mar 11. doi: 10.1038/s41594-025-01516-6. Online ahead of print.

ABSTRACT

The metazoan tRNA ligase complex (tRNA-LC) has essential roles in tRNA biogenesis and unfolded protein response. Its catalytic subunit RTCB contains a conserved active-site cysteine that is susceptible to metal ion-induced oxidative inactivation. The flavin-containing oxidoreductase PYROXD1 preserves the activity of human tRNA-LC in a NAD(P)H-dependent manner, but its protective mechanism remains elusive. Here, we report a cryogenic electron microscopic structure of the human RTCB-PYROXD1 complex, revealing that PYROXD1 directly interacts with the catalytic center of RTCB through its carboxy-terminal tail. NAD(P)H binding and FAD reduction allosterically control PYROXD1 activity and RTCB recruitment, while reoxidation of PYROXD1 enables timed release of RTCB. PYROXD1 interaction is mutually exclusive with Archease-mediated RTCB guanylylation, and guanylylated RTCB is intrinsically protected from oxidative inactivation. Together, these findings provide a mechanistic framework for the protective function of PYROXD1 that maintains the activity of the tRNA-LC under aerobic conditions.

PMID:40069351 | DOI:10.1038/s41594-025-01516-6

Sci Rep. 2025 Mar 11;15(1):8384. doi: 10.1038/s41598-025-92781-4.

ABSTRACT

Eld's deer (Rucervus eldii) is a rare and globally endangered tropical Southeast Asian deer species. There is no research on pathogens in Eld's deer in Hainan, China. This study aimed to understand the virus diversity and novel viruses in Eld's deer, and provided important epidemiological baseline information for conservation of this endangered species. 33 nasal swabs, 33 anal swabs, and 9 wound (bitten by ticks) swabs were collected from 33 wild Eld's deer in a nature reserve in Hainan, which constituted into 5 pools. Based on next-generation sequencing (NGS) and macrogenomic analysis, there were differences in the 5 pools of viral reads, while the overall viral reads were closely related to mammals. The novel papillomavirus (PsPV-HMU-1) and Circular Rep-encoding (replication-associated protein encoding) single-stranded DNA (CRESS DNA) virus (PsaCV-HMU-1) were identified in Eld's deer, with amino acid homology of the less than 77.20% of the L1 and less than 45.43% of the rep, respectively. PsPV-HMU-1 and PsaCV-HMU-1 are relatively independent on their phylogenetic trees, and with the overall prevalence of 24.24% (8/33) and 3.03% (1/33) in Eld's deer, respectively. Our results expanded the viral genomic information and host range, and implied that it is necessary for continued epidemiological surveillance in order to understand pathogenicity and the potential for cross-species transmission of viruses in wild Eld's deer.

PMID:40069308 | DOI:10.1038/s41598-025-92781-4

Sci Rep. 2025 Mar 12;15(1):8465. doi: 10.1038/s41598-025-92942-5.

ABSTRACT

Rice, a staple food consumed by half of the world's population, is severely affected by the combined impact of abiotic and biotic stresses, with the former causing increased susceptibility of the plant to pathogens. Four microarray datasets for drought, salinity, tungro virus, and blast pathogen were retrieved from the Gene Expression Omnibus database. A modular gene co-expression (mGCE) analysis was conducted, followed by gene set enrichment analysis to evaluate the upregulation of module activity across different stress conditions. Over-representation analysis was conducted to determine the functional association of each gene module with stress-related processes and pathways. The protein-protein interaction network of mGCE hub genes was constructed, and the Maximal Clique Centrality (MCC) algorithm was applied to enhance precision in identifying key genes. Finally, genes implicated in both abiotic and biotic stress responses were validated using RT-qPCR. A total of 11, 12, 46, and 14 modules containing 85, 106, 253, and 143 hub genes were detected in drought, salinity, tungro virus, and blast. Modular genes in drought were primarily enriched in response to heat stimulus and water deprivation, while salinity-related genes were enriched in response to external stimuli. For the tungro virus and blast pathogen, enrichment was mainly observed in the defence and stress responses. Interestingly, RPS5, PKG, HSP90, HSP70, and MCM were consistently present in abiotic and biotic stresses. The DEG analysis revealed the upregulation of MCM under the tungro virus and downregulation under blast and drought in resistant rice, indicating its role in viral resistance. HSP70 showed no changes, while HSP90 was upregulated in susceptible rice during blast and drought. PKG increased during drought but decreased in japonica rice under salinity. RPS5 was highly upregulated during blast in both resistant and susceptible rice. The RT-qPCR analysis showed that all five hub genes were upregulated in all treatments, indicating their role in stress responses and potential for crop improvement.

PMID:40069264 | DOI:10.1038/s41598-025-92942-5

Endocr Oncol. 2025 Feb 26;5(1):e240060. doi: 10.1530/EO-24-0060. eCollection 2025 Jan.

ABSTRACT

Medullary thyroid cancer (MTC) is a rare subtype of thyroid cancer originating from parafollicular C-cells of the thyroid. Tyrosine kinase inhibitors are used to treat patients with advanced MTC. Selpercatinib is a highly selective RET inhibitor used in the treatment of advanced RET-mutated MTC, having shown higher potency and fewer side effects compared to multikinase inhibitors in clinical trials. As a relatively new drug, its toxicity profile continues to be characterised. This report describes a case of severe acute hypocalcaemia in a 64-year-old male with advanced MTC treated with selpercatinib. The patient, who had stable hypoparathyroidism, experienced acute hypocalcaemia (corrected calcium 1.4 mmol/L) 2 weeks after initiating selpercatinib, requiring hospitalisation for calcium supplementation and monitoring. Selpercatinib was temporarily withheld and later reintroduced at a lower dose, successfully preventing recurrence of hypocalcaemia. Investigations excluded other common or important causes of hypocalcaemia, which led us to conclude that this could be a drug-related adverse event. This case highlights the need for careful monitoring of electrolyte disturbances in patients on selpercatinib, particularly those with pre-existing hypoparathyroidism. Although rare, the development of hypocalcaemia with RET inhibitors may necessitate dose interruptions and adjustments. Our experience has also illustrated that re-challenge with selpercatinib is feasible with appropriate management strategies.

PMID:40070601 | PMC:PMC11896645 | DOI:10.1530/EO-24-0060

Crit Care. 2025 Mar 11;29(1):108. doi: 10.1186/s13054-025-05331-9.

ABSTRACT

BACKGROUND: Delirium and postoperative cognitive dysfunction (POCD) are common complications post-cardiac surgery, yet no specific medical intervention is currently recommended for prevention. This study aimed to evaluate the efficacy of gastrodin infusion in preventing delirium and POCD in critically ill patients following cardiac surgery.

MATERIAL AND METHODS: A double-blind, randomized, placebo-controlled trial was conducted on patients aged 18-75, scheduled for coronary artery bypass grafting (CABG) surgery, with or without valve replacement. Participants were randomized in a 1:1 ratio to receive gastrodin infusion 600 mg twice daily or placebo from the day of surgery until the postoperative day (POD) 6. The co-primary outcomes were the incidences of delirium and POCD, assessed from ICU admission until POD 7 and at 1 and 3 months postoperatively. This study was registered with the Chinese Clinical Trials Registry (ChiCTR1800020414).

RESULTS: Of 160 randomized participants, 155 were analyzed (77 gastrodin, 78 placebo) according to a modified intention to treat principle. The incidence of postoperative delirium was 19.5% in the gastrodin group and 35.9% in the placebo group, with a significant relative risk of 0.54 (95% CI 0.32-0.93, p = 0.022). The incidence of in-hospital POCD was 2.9% and 4.0% in the placebo and gastrodin groups, respectively. The odds of hospital discharge were significantly greater in the gastrodin group (subhazard ratio, 1.20; 95% CI 1.00-1.84; p = 0.049). Adverse events occurred in 9.1% (7/77) of patients administered gastrodin and 14.1% (11/78) of patients administered the placebo, with none being drug-related.

CONCLUSION: Gastrodin infusion significantly reduced postoperative delirium and improved discharge outcomes in patients undergoing CABG, but larger studies are needed to confirm its efficacy in preventing delirium.

PMID:40069830 | DOI:10.1186/s13054-025-05331-9

Sci Data. 2025 Mar 11;12(1):424. doi: 10.1038/s41597-025-04718-1.

ABSTRACT

Adverse drug events (ADEs) are a major safety issue in clinical trials. Thus, predicting ADEs is key to developing safer medications and enhancing patient outcomes. To support this effort, we introduce CT-ADE, a dataset for multilabel ADE prediction in monopharmacy treatments. CT-ADE encompasses 2,497 drugs and 168,984 drug-ADE pairs from clinical trial results, annotated using the MedDRA ontology. Unlike existing resources, CT-ADE integrates treatment and target population data, enabling comparative analyses under varying conditions, such as dosage, administration route, and demographics. In addition, CT-ADE systematically collects all ADEs in the study population, including positive and negative cases. To provide a baseline for ADE prediction performance using the CT-ADE dataset, we conducted analyses using large language models (LLMs). The best LLM achieved an F1-score of 56%, with models incorporating treatment and patient information outperforming by 21%-38% those relying solely on the chemical structure. These findings underscore the importance of contextual information in ADE prediction and establish CT-ADE as a robust resource for safety risk assessment in pharmaceutical research and development.

PMID:40069213 | DOI:10.1038/s41597-025-04718-1

BDJ Open. 2025 Mar 11;11(1):24. doi: 10.1038/s41405-024-00291-8.

ABSTRACT

BACKGROUND: Drug-associated gingival disorders can negatively impact on oral health. This study aimed to utilize the United States Food and Drug Administration Adverse Event Reporting System (USFDA AERS) to comprehensively assess the associations between medications and specific gingival disorders.

METHODS: Data were extracted from the USFDA AERS from 2004-2024 using Preferred Terms for eight gingival disorders. Reports were deduplicated and disproportionality analysis was conducted using frequentist and Bayesian approaches to detect potential signals. Volcano plots were generated for each gum disorder to identify the drugs with the strongest signals based on the statistical significance and magnitude of association.

RESULTS: A total of 11,465 reports were included. Several anti-osteoporotic drugs, anti-thrombotics, calcium channel blockers and immunosuppressants showed significant associations with multiple gingival disorders. Phenytoin was linked to hypertrophy and bleeding. Stomatological preparations were associated with discoloration and bleeding. Emergent signals were identified with finasteride, COVID-19 vaccine, and levothyroxine with gum disorders.

CONCLUSION: This study highlights the need for increased awareness of oral side effects amongst healthcare providers. Future research should explore the mechanisms of drug-induced gingival disorders and develop interdisciplinary management strategies to enhance oral health in patients on long-term medications.

PMID:40069171 | DOI:10.1038/s41405-024-00291-8

J Cyst Fibros. 2025 Mar 10:S1569-1993(25)00065-7. doi: 10.1016/j.jcf.2025.02.015. Online ahead of print.

ABSTRACT

INTRODUCTION: Functional magnetic resonance imaging (MRI) of the lung usually assesses lung impairment as ventilation defect percentage (VDP). However, VDP only reflects the overall burden of disease and does not characterize the regional distribution (i.e. pattern) of defects. The defect distribution index (DDI) is a metric which shows quantitatively how clustered versus scattered defects are with a higher DDI indicating more clustered defects.

AIM: To assess the applicability and validity of the DDI to 129Xe-MRI and PREFUL-MRI of CF lung disease.

METHODS: The DDI algorithm was applied to fractional ventilation maps previously acquired with 129Xe-MRI and PREFUL-MRI of 37 children with CF and 13 healthy controls.

RESULTS: The calculation of DDI was feasible for all MRI data. DDI was significantly higher in patients with CF compared to healthy controls (mean difference [95 % CI] 129Xe-MRI DDI60 %mean -1.94 [-2.86 - -1.02], p=0.0001), strongly correlated with other functional outcomes such as VDP and the lung clearance index, and decreased significantly in CF patients with pulmonary exacerbations after antibiotic treatment (e.g. 129Xe-MRI DDI60 % mean -1.03 [-0.44 - -1.63], p=0.002).

CONCLUSION: The DDI is applicable to functional 129Xe-MRI and PREFUL-MRI data providing complementary information to VDP by assessing defect distribution rather than defect size. It shows meaningful clinimetric properties and improves with treatment. The DDI shows potential as a parameter for comprehensive monitoring of CF lung disease and treatment.

PMID:40069051 | DOI:10.1016/j.jcf.2025.02.015