Methods Mol Biol. 2025;2914:275-302. doi: 10.1007/978-1-0716-4462-1_20.

ABSTRACT

Cerebrospinal fluid (CSF) is a source of valuable information concerning brain disorders. The technical advances of high throughput omics platforms to analyze body fluids can generate a huge amount of data, whose translation of the biological meaning can be a challenge. Several bioinformatics tools have emerged to help handle this data from a systems biology perspective. Herein, we describe a step-by-step tutorial for CSF proteome data analysis in the set of neurodegenerative diseases using: (i) ShinyGO webtool to perform functional enrichment analysis envisioning the characterization of the biological pathways and processes deregulated in neurodegenerative diseases including Alzheimer's and Parkinson's diseases; (ii) Cytoscape to map disease-specific proteins based on evidence from proteomics; (iii) DisGeNET to identify the proteins more strongly and more specifically associated with neurodegenerative diseases to date; (iv) STRING to identify putative therapeutic targets through a combined protein-protein interaction and network topological analyses. This step-by-step guide might help researchers to better characterize disease pathogenesis and to identify putative disease biomarkers and therapeutic targets.

PMID:40167925 | DOI:10.1007/978-1-0716-4462-1_20

Metabolomics. 2025 Apr 1;21(2):48. doi: 10.1007/s11306-025-02247-x.

NO ABSTRACT

PMID:40167843 | DOI:10.1007/s11306-025-02247-x

Semin Immunopathol. 2025 Apr 1;47(1):23. doi: 10.1007/s00281-025-01049-6.

ABSTRACT

Barrier organs such as the gastrointestinal tract, lungs, and skin are colonized by diverse microbial strains, including bacteria, viruses, and fungi. These microorganisms, collectively known as the commensal microbiota, play critical roles in maintaining health by defending against pathogens, metabolizing nutrients, and providing essential metabolites. In the gut, commensal-derived antigens are frequently sensed by the intestinal immune system. Maintaining tolerance toward these beneficial microbial species is crucial, as failure to do so can lead to chronic inflammatory conditions like inflammatory bowel disease (IBD) and can even affect systemic immune or metabolic health. The immune system carefully regulates responses to commensals through various mechanisms, including the induction of anti-inflammatory CD4⁺ T cell responses. Foxp3⁺ regulatory T cells (Foxp3+ Tregs) and Type 1 regulatory T cells (Tr1) play a major role in promoting tolerance, as both cell types can produce the anti-inflammatory cytokine IL-10. In addition to these regulatory T cells, effector T cell subsets, such as Th17 cells, also adopt anti-inflammatory functions within the intestine in response to the microbiota. This process of anti-inflammatory CD4+ T cell induction is heavily influenced by the microbiota and their metabolites. Microbial metabolites affect intestinal epithelial cells, promoting the secretion of anti-inflammatory mediators that create a tolerogenic environment. They also modulate intestinal dendritic cells (DCs) and macrophages, inducing a tolerogenic state, and can interact directly with T cells to drive anti-inflammatory CD4⁺ T cell functionality. The disrupted balance of these signals may result in chronic inflammation, with broader implications for systemic health. In this review, we highlight the intricate interplays between commensal microorganisms and the immune system in the gut. We discuss how the microbiota influences the differentiation of commensal-specific anti-inflammatory CD4⁺ T cells, such as Foxp3⁺ Tregs, Tr1 cells, and Th17 cells, and explore the mechanisms through which microbial metabolites modulate these processes. We further discuss the innate signals that prime and commit these cells to an anti-inflammatory fate.

PMID:40167791 | DOI:10.1007/s00281-025-01049-6

Funct Integr Genomics. 2025 Apr 1;25(1):78. doi: 10.1007/s10142-025-01588-z.

ABSTRACT

Metabolic engineering of lipids in crops presents a promising strategy to enhance resilience against environmental stressors while improving nutritional quality. By manipulating key enzymes in lipid metabolism, introducing novel genes, and utilizing genome editing technologies, researchers have improved crop tolerance to abiotic stresses such as drought, salinity, and extreme temperatures. Additionally, modified lipid pathways contribute to resistance against biotic stresses, including pathogen attacks and pest infestations. Engineering multiple stress-resistance traits through lipid metabolism offers a holistic approach to strengthening crop resilience amid changing environmental conditions. Beyond stress tolerance, lipid engineering enhances the nutritional profile of crops by increasing beneficial lipids such as omega-3 fatty acids, vitamins, and antioxidants. This dual approach not only improves crop yield and quality but also supports global food security by ensuring sustainable agricultural production. Integrating advanced biotechnological tools with a deeper understanding of lipid biology paves the way for developing resilient, nutrient-rich crops capable of withstanding climate change and feeding a growing population.

PMID:40167787 | DOI:10.1007/s10142-025-01588-z

Adv Sci (Weinh). 2025 Apr 1:e2412921. doi: 10.1002/advs.202412921. Online ahead of print.

ABSTRACT

HDAC6 is integral to the regulation of primary cilia, which are specialized structures that serve as crucial signaling hubs for cellular communication and environmental response. These ciliary functions are essential for maintaining cellular homeostasis and orchestrating developmental processes. Dysregulation of HDAC6 activity is implicated in ciliopathies, a group of disorders characterized by defective ciliary structure or function, resulting in widespread organ involvement and significant morbidity. This review provides a comprehensive examination of the molecular dynamics of HDAC6 in the context of ciliogenesis and ciliopathies, emphasizing its dual role in the deacetylation of microtubules and regulation of the ciliary axoneme. Furthermore, HDAC6 interacts with key signaling molecules, modulating processes ranging from cell cycle regulation to inflammatory responses, which highlights its central role in cellular physiology and pathology. The therapeutic potential of HDAC6 inhibitors has been explored, with promising results in various disease models, including retinal and renal ciliopathies, highlighting their ability to restore normal ciliary function. This analysis not only underscores the critical importance of HDAC6 in maintaining ciliary integrity but also illustrates how targeting the HDAC6-cilia axis could provide a groundbreaking approach to treating these complex disorders. In doing so, this review sets the stage for future investigations into HDAC6-targeted therapies, potentially transforming the clinical management of ciliopathies and significantly improving patient outcomes.

PMID:40167251 | DOI:10.1002/advs.202412921

Circulation. 2025 Apr 1. doi: 10.1161/CIRCULATIONAHA.121.058621. Online ahead of print.

ABSTRACT

BACKGROUND: Gene mutations are responsible for a sizeable proportion of cases of heart failure. However, the number of patients with any specific mutation is small. Repositioning of existing US Food and Drug Administration-approved compounds to target specific mutations is a promising approach to efficient identification of new therapies for these patients.

METHODS: The National Institutes of Health Library of Integrated Network-Based Cellular Signatures database was interrogated to identify US Food and Drug Administration-approved compounds that demonstrated the ability to reverse the transcriptional effects of LMNA knockdown. Top hits from this screening were validated in vitro with patient-specific induced pluripotent stem cell-derived cardiomyocytes combined with force measurement, gene expression profiling, electrophysiology, and protein expression analysis.

RESULTS: Several angiotensin receptor blockers were identified from our in silico screen. Of these, olmesartan significantly elevated the expression of sarcomeric genes and rate and force of contraction and ameliorated arrhythmogenic potential. In addition, olmesartan exhibited the ability to reduce phosphorylation of extracellular signal-regulated kinase 1 in LMNA-mutant induced pluripotent stem cell-derived cardiomyocytes.

CONCLUSIONS: In silico screening followed by in vitro validation with induced pluripotent stem cell-derived models can be an efficient approach to identifying repositionable therapies for monogenic cardiomyopathies.

PMID:40166828 | DOI:10.1161/CIRCULATIONAHA.121.058621

medRxiv [Preprint]. 2025 Mar 24:2025.03.19.25324271. doi: 10.1101/2025.03.19.25324271.

ABSTRACT

BACKGROUND: Randomized controlled trials (RCTs) provide the highest level of clinical evidence but are often limited by cost, time, and ethical constraints. Emulating RCTs using real-world data (RWD) offers a complementary approach to evaluate the treatment effect in a real clinical setting. This study aims to replicate clinical trials based on Mayo Clinic Platform (MCP) electronic health records (EHRs) and emulation frameworks. In this study, we address two key questions: (1) whether clinical trials can be feasibly replicated using the MCP, and (2) whether trial emulation produces consistent conclusions based on real clinical data compared to the original randomized controlled trials RCTs.

METHODS: We conducted a retrospective observational study with an adaption of trial emulation. To assess feasibility, we applied a refined filtering method to identify trials suitable for emulation. The emulation protocol was carefully designed on top of the original RCT protocol to balance scientific rigor and practical feasibility. To minimize potential selection bias and enhance comparability between groups, we employed propensity score matching (PSM) as a statistical adjustment method.

RESULTS: Based on our predefined search criteria targeting phase 3 trials focused on drug repurposing for heart failure patients, we initially identified 27 eligible trials. After a two-step manual review of the original eligibility criteria and extraction of the patient cohorts based on MCP visualizer, we further narrowed our selection to the WARCEF trial, as it provided an adequate sample size for the emulation within the MCP. The experiment compares the WARCEF trial and a simulation study on Aspirin vs. Warfarin. The original study (smaller sample) found no significant difference (HR = 1.016, p < 0.91). The simulation (larger sample) showed a slightly higher HR (1.161) with borderline significance (p < 0.052, CI: 0.999-1.350), suggesting a possible increased risk with Warfarin, though not conclusive.

CONCLUSION: RCT emulation enhances real-world evidence (RWE) for clinical decision-making but faces limitations from confounding, missing data, and cohort biases. Future research should explore machine learning-driven patient matching and scalable RCT emulation. This study supports the integration of RWE into evidence-based medicine.

PMID:40166580 | PMC:PMC11957179 | DOI:10.1101/2025.03.19.25324271

medRxiv [Preprint]. 2025 Mar 23:2025.03.22.25324223. doi: 10.1101/2025.03.22.25324223.

ABSTRACT

Drug development is a long and costly process, and repurposing existing drugs for use toward a different disease or condition may serve as a cost-effective alternative. As drug targets with genetic support have a doubled success rate, genetics-informed drug repurposing holds promise in translating genetic findings into therapeutics. In this study, we developed a Genetics Informed Network-based Drug Repurposing via in silico Perturbation (GIN-DRIP) framework and applied the framework to repurpose drugs for type-2 diabetes (T2D). In GIN-DRIP for T2D, it integrates multi-level omics data to translate T2D GWAS signals into a genetics-informed network that simultaneously encodes gene importance scores and a directional effect (up/down) of risk genes for T2D; it then bases on the GIN to perform signature matching with drug perturbation experiments to identify drugs that can counteract the effect of T2D risk alleles. With this approach, we identified 3 high-confidence FDA-approved candidate drugs for T2D, and validated telmisartan, an anti-hypertensive drug, in our EHR data with over 3 million patients. We found that telmisartan users were associated with a reduced incidence of T2D compared to users of other anti-hypertensive drugs and non-users, supporting the therapeutic potential of telmisartan for T2D. Our framework can be applied to other diseases for translating GWAS findings to aid drug repurposing for complex diseases.

PMID:40166562 | PMC:PMC11957187 | DOI:10.1101/2025.03.22.25324223

medRxiv [Preprint]. 2025 Mar 17:2025.03.17.25324106. doi: 10.1101/2025.03.17.25324106.

ABSTRACT

BACKGROUND: Complex diseases may share portions of their polygenic architectures which can be leveraged to identify drug targets with low off-target potential or repurposable candidates. However, the literature lacks methods which can make these inferences at scale using publicly available data.

METHODS: We introduce a Bayesian model to estimate the polygenic structure of a trait using only gene-based association test statistics from GWAS summary data and returns gene-level posterior risk probabilities (PRPs). PRPs were used to infer shared polygenicity between 496 trait pairs and we introduce measures that can prioritize drug targets with low off-target effects or drug repurposing potential.

RESULTS: Across 32 traits, we estimated that 69.5 to 97.5% of disease-associated genes are shared between multiple traits, and the estimated number of druggable genes that were only associated with a single disease ranged from 1 (multiple sclerosis) to 59 (schizophrenia). Estimating the shared genetic architecture of ALS with all other traits identified the KIT gene as a potentially harmful drug target because of its deleterious association with triglycerides, but also identified TBK1 and SCN11B as putatively safer because of their non-association with any of the other 31 traits. We additionally found 21 genes which are candidate repourposable targets for Alzheimer's disease (AD) (e.g., PLEKHA1, PPIB ) and 5 for ALS (e.g., GAK, DGKQ ).

CONCLUSIONS: The sets of candidate drug targets which have limited off-target potential are generally smaller compared to the sets of pleiotropic and putatively repurposable drug targets, but both represent promising directions for future experimental studies.

PMID:40166559 | PMC:PMC11957083 | DOI:10.1101/2025.03.17.25324106

Front Pharmacol. 2025 Mar 17;16:1537912. doi: 10.3389/fphar.2025.1537912. eCollection 2025.

ABSTRACT

BACKGROUND AND PURPOSE: The coronavirus disease 2019 (COVID-19) pandemic has devastated global health and the economy, underscoring the urgent need for extensive research into the mechanisms of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) viral entry and the development of effective therapeutic interventions.

EXPERIMENTAL APPROACH: We established a cell line expressing human angiotensin-converting enzyme 2 (ACE2). We used it as a model of pseudotyped viral entry using murine leukemia virus (MLV) expressing SARS-CoV-2 spike (S) protein on its surface and firefly luciferase as a reporter. We screened an U.S. Food and Drug Administration (FDA)-approved compound library for inhibiting ACE2-dependent SARS-CoV-2 pseudotyped viral entry and identified several drug-repurposing candidates.

KEY RESULTS: We identified 18 drugs and drug candidates, including 14 previously reported inhibitors of viral entry and four novel candidates. Pyridoxal 5'-phosphate, Dovitinib, Adefovir dipivoxil, and Biapenem potently inhibit ACE2-dependent viral entry with inhibitory concentration 50% (IC50) values of 57nM, 74 nM, 130 nM, and 183 nM, respectively.

CONCLUSION AND IMPLICATIONS: We identified four novel FDA-approved candidate drugs for anti-SARS-CoV-2 combination therapy. Our findings contribute to the growing body of evidence supporting drug repurposing as a viable strategy for rapidly developing COVID-19 treatments.

PMID:40166473 | PMC:PMC11955658 | DOI:10.3389/fphar.2025.1537912

bioRxiv [Preprint]. 2025 Mar 18:2025.03.18.642440. doi: 10.1101/2025.03.18.642440.

ABSTRACT

Human topoisomerase III beta (TOP3B) is a type IA topoisomerase that can change the topology of DNA and RNA substrates via a phosphotyrosine covalent intermediate. TOP3B has been shown to be required for the efficient replication of certain positive-sense ssRNA viruses including Dengue. We applied molecular dynamics simulation combined with docking studies to identify potential inhibitors of TOP3B from a library comprised of drugs that are FDA-approved or undergoing clinical trials for potential drug repurposing. Topoisomerase activity assay of the top virtual screening hits showed that bemcentinib, a compound known to target the AXL receptor tyrosine kinase, can inhibit TOP3B relaxation activity. Additional small molecules that share the N5 , N3 -1 H -1,2,4-triazole-3,5-diamine moiety of bemcentinib were synthesized and tested for inhibition of TOP3B relaxation activity. Five of these molecules showed comparable IC 50 as bemcentinib for inhibition of TOP3B. However, these five molecules had less selectivity towards TOP3B inhibition versus bemcentinib when inhibition of the type IB human topoisomerase I was com-pared. These results suggest that exploration of tyrosine kinase inhibitors and their analogs may allow the identification of novel topoisomerase inhibitors.

PMID:40166181 | PMC:PMC11956937 | DOI:10.1101/2025.03.18.642440

Front Immunol. 2025 Mar 17;16:1537428. doi: 10.3389/fimmu.2025.1537428. eCollection 2025.

ABSTRACT

Pemphigoid diseases constitute a group of organ-specific autoimmune diseases characterized and caused by autoantibodies targeting autoantigens expressed in the skin and mucous membranes. Current therapeutic options are still based on unspecific immunosuppression that is associated with severe adverse events. Biologics, targeting the IL4-pathway or IgE are expected to change the treatment landscape of pemphigoid diseases. However, clinical studies demonstrated that targeting these pathways alone is most likely not sufficient to meet patient and healthcare partitioners expectations. Hence, model systems are needed to identify and validate novel therapeutic targets in pemphigoid diseases. These include pre-clinical animal models, in vitro and ex vivo model systems, hypothesis-driven drug repurposing, as well as exploitation of real-world-data. In this review, we will highlight the medical need for pemphigoid diseases, and in-depth discuss the advantages and disadvantages of the available pemphigoid disease model systems. Ultimately, we discuss how rapid translation can be achieved for the benefit of the patients.

PMID:40165962 | PMC:PMC11955494 | DOI:10.3389/fimmu.2025.1537428

Orphanet J Rare Dis. 2025 Apr 1;20(1):150. doi: 10.1186/s13023-025-03656-w.

ABSTRACT

Diagnosing rare diseases is challenging due to their low prevalence, diverse presentations, and limited recognition, often leading to diagnostic delays and errors. This study evaluates the effectiveness of multiple large language models (LLMs) in identifying rare diseases, comparing their performance with that of human physicians using real clinical cases. We analyzed 152 rare disease cases from the Chinese Medical Case Repository using four LLMs: ChatGPT-4o, Claude 3.5 Sonnet, Gemini Advanced, and Llama 3.1 405B. Overall, the LLMs performed better than human physicians, and Claude 3.5 Sonnet achieved the highest accuracy at 78.9%, significantly surpassing the accuracy of human physicians, which was 26.3%. These findings suggest that LLMs can improve rare disease diagnosis and serve as valuable tools in clinical settings, particularly in regions with limited resources. However, further validation and careful consideration of ethical and privacy issues are necessary for their effective integration into medical practice.

PMID:40165285 | DOI:10.1186/s13023-025-03656-w

Front Pharmacol. 2025 Mar 17;16:1553536. doi: 10.3389/fphar.2025.1553536. eCollection 2025.

ABSTRACT

BACKGROUND: Pharmacogenomics offers a possibility of anticipating drug response based on individuals' genetic profiles and represents a step toward implementation of personalized treatment through routine genetic testing. Development of highthroughput sequencing technologies aided identification and interpretation of variants in many pharmacogenes simultaneously. Nonetheless, the integration of pharmacogenomics into clinical practice is arduous, partly due to insufficient knowledge of ethnic pharmacogenetic data. The aim of our study was to assemble the most comprehensive pharmacogenomics landscape of the Serbian population so far.

METHODS: We used genomic data of 881 individuals from Serbia obtained by clinical and whole exome sequencing. Raw sequencing files were processed using an in-house pipeline for alignment and variant calling. For annotation of pharmacogenetics star alleles and determination of phenotypes, we used the PharmCAT and Stargazer tools. Star allele and phenotype frequencies were calculated and compared to worldwide and European populations. Population differentiation was presented through calculation of Wright's fixation index.

RESULTS: Our results showed that population differentiation was the highest between the Serbian and the worldwide population. In the Serbian population, the most relevant pharmacogenes in terms of star allele frequencies and actionable phenotypes were CYP2B6, NAT2, SLCO1B1, UGT1A1 and VKORC1, that had significantly different distribution compared to other European populations.

CONCLUSION: In conclusion, significant differences in frequencies of pharmacogenetic phenotypes that influence response to several drug categories including statins and antidepressants indicate that inclusion of data relevant for drug response to genetic reports would be beneficial in the Serbian population. Implementation of pharmacogenetic testing could be achieved through analysis of clinical and whole exome sequencing data.

PMID:40166472 | PMC:PMC11955590 | DOI:10.3389/fphar.2025.1553536

Front Med (Lausanne). 2025 Mar 17;12:1535099. doi: 10.3389/fmed.2025.1535099. eCollection 2025.

ABSTRACT

INTRODUCTION: Gaucher disease (GD), a lysosomal storage disorder, results from the accumulation of glycosphingolipids due to deficient lysosomal glucocerebrosidase activity. This pathological accumulation triggers immune activation, which paradoxically induces UDPglucose ceramide glucosyltransferase (UGCG), further exacerbating the metabolic defect. Eliglustat, a highly specific inhibitor of UGCG, functions as a substrate reduction therapy (SRT) and has demonstrated efficacy in reversing GD manifestations in clinical trials and real-world settings. Despite its established safety profile, preclinical studies have shown that supratherapeutic concentrations of eliglustat can inhibit ion channels involved in cardiac electrophysiology. However, pharmacogenomic-guided dosing ensures therapeutic efficacy while maintaining a wide safety margin, minimizing such risks. Nevertheless, lingering concerns regarding cardiac safety have persisted, particularly in patients with preexisting cardiac comorbidities.

METHODS: We report a single-center experience of eliglustat use in 13 patients with type 1 Gaucher disease (GD1) and concurrent cardiac comorbidities. Patients underwent standard cardiac evaluations, including electrocardiogram (EKG) with QTc interval assessment and echocardiogram. Eliglustat dosing was guided by CYP2D6 metabolizer status, and potential drug-drug interactions (DDIs) were carefully monitored.

RESULTS: Cardiac comorbidities included prior myocardial infarction (n = 2), aortic stenosis (n = 2), atrial fibrillation (n = 2), Wolff-Parkinson-White syndrome (n = 1), pericarditis (n = 1), premature ventricular complexes (n = 2), severe pulmonary arterial hypertension with right heart strain (n = 1), mitral annular calcification with diastolic dysfunction (n = 1), and mildly prolonged QTc interval (n = 1). No patients experienced arrhythmia, QTc prolongation, or arrhythmia-related symptoms. Treatment discontinuation was not required. All patients achieved expected therapeutic outcomes, as evidenced by serial reductions in glucosylsphingosine (GlcSph) levels and other disease indicators.

CONCLUSION: This study represents the first real-world clinical evidence evaluating Eliglustat's cardiac safety in a high-risk GD1 population. Unlike prior theoretical concerns derived from in vitro ion channel studies, our findings demonstrate that Eliglustat does not induce clinically significant cardiac events when administered according to pharmacogenomic guidelines. The misinformation regarding Eliglustat's cardiotoxicity, largely driven by speculative interpretations rather than clinical data, is effectively countered by our findings, which show no significant QT prolongation or arrhythmias over a median treatment duration of 8 years.

PMID:40166071 | PMC:PMC11956841 | DOI:10.3389/fmed.2025.1535099

Am J Chin Med. 2025 Mar 29:1-30. doi: 10.1142/S0192415X25500223. Online ahead of print.

ABSTRACT

Bile acid metabolism mediated by gut microbiota is significantly related to immunity regulation that plays an important role in the development and treatment of inflammatory bowel disease (IBD). Our previous study has demonstrated that Panax notoginseng saponins (PNS) alleviate colitis due to the regulation of T helper 17/Regulatory T cells (Th17/Treg) balance via gut microbiota. However, the effects and mechanism of PNS on colitis pertinent to bile acid metabolism mediated by gut microbiota remain elusive. This study aims to investigate the anti-colitis mechanism of PNS by regulating the Th17/Treg balance pertinent to gut microbiota-bile acid metabolism. Results showed that PNS significantly decreased the relative abundance of Allobaculum, Dubosiella, Muribaculum, and Alistipes, and up-regulated the relative contents of conjugated bile acids, such as TCA and TCDCA. Fecal microbiota transplantation (FMT) showed that the gut microbiota remodeled by PNS had a regulatory effect on bile acid metabolism, and up-regulated the relative contents of TCA and TCDCA, which alleviated IBD and promoted Treg cell expression in vivo and in vitro. Taken together, PNS could reshape the profiling of gut microbiota to generate more TCA and TCDCA, which improve the balance of Th17/Treg to exert anti-IBD effects.

PMID:40165428 | DOI:10.1142/S0192415X25500223

J Pediatr Gastroenterol Nutr. 2025 Mar 31. doi: 10.1002/jpn3.70029. Online ahead of print.

ABSTRACT

OBJECTIVES: We determined the prevalence of anemia and its characteristics in children with newly diagnosed inflammatory bowel disease (IBD) and investigated its trend during follow-up.

METHODS: An observational, multicenter cohort study of IBD children with anemia at the diagnosis enrolled in the Italian Society of Pediatric Gastroenterology, Hepatology, and Nutrition IBD registry. Data were collected at the diagnosis and at 1 year.

RESULTS: Five hundred eighty-nine (295 Crohn's disease [CD] [50%] and 294 ulcerative colitis [UC]/IBD unclassified [IBDU] [50%]) of 1634 patients with IBD presented with anemia (36%). Anemia rate was higher in CD than in UC (39% vs. 33%, p = 0.009), and most patients had moderate anemia (55%). Children with CD had higher rates of mild anemia than UC (38% vs. 33%, p < 0.0001), while severe anemia was more common in UC (13% vs. 6%, p = 0.001). In CD, lower age at the diagnosis and lower albumin level correlated with anemia severity (p = 0.0007 and <0.0001, respectively). In UC, severe disease was more common in patients with severe anemia compared to those with mild and moderate anemia (20.6% vs. 43.6%, p = 0.01; 17% vs. 43.6%, p = 0.001). At 1 year, 99 children (22.9%) were persistently anemic and were characterized by a more severe disease compared to those who had resolved their anemia.

CONCLUSIONS: More than one third of IBD children present with anemia, most commonly moderate. Severe anemia is more common in UC compared to CD. One in four patients is still anemic after 1 year from the diagnosis, suggesting inadequate attention to the issue and the need for dedicated therapeutic management and careful monitoring.

PMID:40165528 | DOI:10.1002/jpn3.70029

Stat Methods Med Res. 2025 Mar 31:9622802251316971. doi: 10.1177/09622802251316971. Online ahead of print.

ABSTRACT

G-formula is a popular approach for estimating the effects of time-varying treatments or exposures from longitudinal data. G-formula is typically implemented using Monte-Carlo simulation, with non-parametric bootstrapping used for inference. In longitudinal data settings missing data are a common issue, which are often handled using multiple imputation, but it is unclear how G-formula and multiple imputation should be combined. We show how G-formula can be implemented using Bayesian multiple imputation methods for synthetic data, and that by doing so, we can impute missing data and simulate the counterfactuals of interest within a single coherent approach. We describe how this can be achieved using standard multiple imputation software and explore its performance using a simulation study and an application from cystic fibrosis.

PMID:40165440 | DOI:10.1177/09622802251316971

ArXiv [Preprint]. 2025 Mar 20:arXiv:2503.16706v1.

ABSTRACT

A recently proposed scatter-window and deep learning-based attenuation compensation (AC) method for myocardial perfusion imaging (MPI) by single-photon emission computed tomography (SPECT), namely CTLESS, demonstrated promising performance on the clinical task of myocardial perfusion defect detection with retrospective data acquired on SPECT scanners from a single vendor. For clinical translation of CTLESS, it is important to assess the generalizability of CTLESS across different SPECT scanners. For this purpose, we conducted a virtual imaging trial, titled in silico imaging trial to assess generalizability (ISIT-GEN). ISIT-GEN assessed the generalizability of CTLESS on the cardiac perfusion defect detection task across SPECT scanners from three different vendors. The performance of CTLESS was compared with a standard-of-care CT-based AC (CTAC) method and a no-attenuation compensation (NAC) method using an anthropomorphic model observer. We observed that CTLESS had receiver operating characteristic (ROC) curves and area under the ROC curves similar to those of CTAC. Further, CTLESS was observed to significantly outperform the NAC method across three scanners. These results are suggestive of the inter-scanner generalizability of CTLESS and motivate further clinical evaluations. The study also highlights the value of using in silico imaging trials to assess the generalizability of deep learning-based AC methods feasibly and rigorously.

PMID:40166744 | PMC:PMC11957238

medRxiv [Preprint]. 2025 Mar 20:2025.03.18.25324199. doi: 10.1101/2025.03.18.25324199.

ABSTRACT

BACKGROUND: Accurate delineation of orodental structures on radiotherapy CT images is essential for dosimetric assessments and dental decisions. We propose a deep-learning auto-segmentation framework for individual teeth and mandible/maxilla sub-volumes aligned with the ClinRad ORN staging system.

METHODS: Mandible and maxilla sub-volumes were manually defined, differentiating between alveolar and basal regions, and teeth were labelled individually. For each task, a DL segmentation model was independently trained. A Swin UNETR-based model was used for the mandible sub-volumes. For the smaller structures (e.g., teeth and maxilla sub-volumes) a two-stage segmentation model first used the ResUNet to segment the entire teeth and maxilla regions as a single ROI that was then used to crop the image input of the Swin UNETR. In addition to segmentation accuracy and geometric precision, a dosimetric comparison was made between manual and model-predicted segmentations.

RESULTS: Segmentation performance varied across sub-volumes - mean Dice values of 0.85 (mandible basal), 0.82 (mandible alveolar), 0.78 (maxilla alveolar), 0.80 (upper central teeth), 0.69 (upper premolars), 0.76 (upper molars), 0.76 (lower central teeth), 0.70 (lower premolars), 0.71 (lower molars) - and exhibited limited applicability in segmenting teeth and sub-volumes often absent in the data. Only the maxilla alveolar central sub-volume showed a statistically significant dosimetric difference (Bonferroni-adjusted p-value = 0.02).

CONCLUSION: We present a novel DL-based auto-segmentation framework of orodental structures, enabling spatial localization of dose-related differences in the jaw. This tool enhances image-based bone injury detection, including ORN, and improves clinical decision-making in radiation oncology and dental care for head and neck cancer patients.

PMID:40166584 | PMC:PMC11957087 | DOI:10.1101/2025.03.18.25324199