Nat Methods. 2025 Apr 29. doi: 10.1038/s41592-025-02699-y. Online ahead of print.

NO ABSTRACT

PMID:40301624 | DOI:10.1038/s41592-025-02699-y

Sci Rep. 2025 Apr 29;15(1):15012. doi: 10.1038/s41598-025-99620-6.

ABSTRACT

This study developed and evaluated a deep learning (DL)-based system for automatically measuring talar tilt and anterior talar translation on weight-bearing ankle radiographs, which are key parameters in diagnosing ankle joint instability. The system was trained and tested using a dataset comprising of 1,452 anteroposterior radiographs (mean age ± standard deviation [SD]: 43.70 ± 22.60 years; age range: 6-87 years; males: 733, females: 719) and 2,984 lateral radiographs (mean age ± SD: 44.37 ± 22.72 years; age range: 6-92 years; male: 1,533, female: 1,451) from a total of 4,000 patients, provided by the National Information Society Agency. Patients who underwent joint fusion, bone grafting, or joint replacement were excluded. Statistical analyses, including correlation coefficient analysis and Bland-Altman plots, were conducted to assess the agreement and consistency between the DL-calculated and clinician-assessed measurements. The system demonstrated high accuracy, with strong correlations for talar tilt (Pearson correlation coefficient [r] = 0.798 (p < .001); intraclass correlation coefficient [ICC] = 0.797 [95% CI 0.74, 0.82]; concordance correlation coefficient [CCC] = 0.796 [95% CI 0.69, 0.85]; mean absolute error [MAE] = 1.088° [95% CI 0.06°, 1.14°]; mean square error [MSE] = 1.780° [95% CI 1.69°, 2.73°]; root mean square error [RMSE] = 1.374° [95% CI 1.31°, 1.44°]; 95% limit of agreement [LoA], 2.0° to - 2.3°) and anterior talar translation (r = .862 (p < .001); ICC = 0.861 [95% CI 0.84, 0.89]; CCC = 0.861 [95% CI 0.86, 0.89]; MAE = 0.468 mm [95% CI 0.42 mm, 0.51 mm]; MSE = 0.551 mm [95% CI 0.49 mm, 0.61 mm]; RMSE = 0.742 mm [95% CI 0.69 mm, 0.79 mm]; 95% LoA, 1.5 mm to - 1.3 mm). These results demonstrate the system's capability to provide objective and reproducible measurements, supporting clinical interpretation of ankle instability in routine radiographic practice.

PMID:40301608 | DOI:10.1038/s41598-025-99620-6

BMC Pulm Med. 2025 Apr 29;25(1):205. doi: 10.1186/s12890-025-03680-3.

ABSTRACT

BACKGROUND: Surgery resection would improve idiopathic pulmonary fibrosis (IPF) patients with early-stage lung cancer (LC). However, most associated studies were published from surgeons. Interstitial lung disease (ILD) physicians involved in perioperative management would be helpful for improving patients with idiopathic pulmonary fibrosis combined with lung cancer (IPF-LC). To enhance the understanding of the clinical characteristics presented by patients with IPF-LC who have undergone surgical resection, and to explore the factors linked to unfavorable prognosis, our ILD physicians conducted this study.

METHODS: We retrospectively examined clinical records of IPF-LC patients at Peking Union Medical College Hospital from January 2014 to December 2023.Data related to clinical manifestations and treatment methods were collected. Patients underwent routine follow-up through clinical assessments and telephone consultations. The demographic, clinical, and laboratory features of 12 surviving patients and 8 deceased patients were comparatively analysed.

RESULTS: There were 30 males and 2 females, aged from 49 years to 82 years. Twenty-eight patients had a history of smoking. Twenty-five patients had at least one comorbidity and emphysema was the most common. IPF was diagnosed before LC in 8 patients but none of them were prescribed with anti-fibrotic medications. Twenty-four patients were simultaneously diagnosed with LC and IPF, and 7 of them were prescribed anti-fibrotic medications. After surgery, 27 patients were pathologically diagnosed with non-small cell lung cancer and 26 patients were classified as stage I or II lung cancer. During follow-up, 8 patients died, 12 patients lost follow-up and 12 patients survived. Among the 8 deceased patients, 5 patients died from acute exacerbation of IPF, one died from cancer progression and 2 died from surgical complications. The serum Cyfra211 level was higher and the lung cancer stage was more advanced in the non-survival group than in the survival group.

CONCLUSION: Most of our IPF-LC patients were elderly males with a history of smoking and had at least one comorbidity. Most of them were diagnosed with IPF and LC simultaneously. However, only one fifth were prescribed with pirfenidone or nintedanib. Acute exacerbation of IPF was the main cause of death. Similar to the LC patients, higher serum Cyfra211 levels and more advanced lung cancer stages were associated with a poor prognosis for our enrolled IPF-LC patients.

CLINICAL TRIAL NUMBER: Not applicable.

PMID:40301827 | DOI:10.1186/s12890-025-03680-3

Transplant Proc. 2025 Apr 28:S0041-1345(25)00229-5. doi: 10.1016/j.transproceed.2025.03.026. Online ahead of print.

ABSTRACT

BACKGROUND: Lung transplantation is the optimal treatment choice, while extracorporeal membrane oxygenation (ECMO) provides cardiopulmonary support during the perioperative period of lung transplantation. Currently, there is no reported research on the ECMO withdrawal and duration of mechanical ventilation (MV) in idiopathic pulmonary fibrosis (IPF) patients undergoing lung transplantation. Therefore, this study aims to evaluate the impact of ECMO duration on prolonged mechanical ventilation (PMV) time in patients, attempting to explore the relationship between the two.

METHODS: This study included 170 patients with IPF who underwent lung transplantation under ECMO technology. The patients were divided into normal and delayed groups based on the ECMO application time of 72 hours. A multifactor logistic regression analysis was conducted to explore the independent risk factors for PMV time, and restricted cubic spline (RCS) was used to investigate the relationship between ECMO application time and MV time. Receptor operating characteristics (ROC) were further used to find the cut-off value of ECMO application time to predict PMV time.

RESULTS: In the normal group, there were 135 cases, of which 79.25% (107 cases) were males and 20.74% (28 cases) were females, whereas in the delayed group, there were 35 cases, of which 57.14% (20 cases) were males and 42.86% (15 cases) were females. In the RCS curves, there was a nonlinear correlation between the duration of ECMO application and the duration of MV, which tended to increase as the duration of ECMO application increased. According to univariate and multivariate logistic analyses, ECMO application time was an influential factor in the occurrence of PMV time, in which the OR of PMV time was 2.02 (95% CI 1.11,1.63, P = .001) when ECMO application time was ≥ 52.01 hours.

CONCLUSION: After lung transplantation, there is a nonlinear relationship between the application time of ECMO and MV time in patients with IPF. The application time of ECMO can predict well the extension of MV in patients during ICU stay. Therefore, clinicians can assess the duration of MV in patients with IPF based on the application time of ECMO, further avoiding complications related to MV.

PMID:40300905 | DOI:10.1016/j.transproceed.2025.03.026

Zhonghua Jie He He Hu Xi Za Zhi. 2025 May 12;48(5):481-486. doi: 10.3760/cma.j.cn112147-20241018-00621.

ABSTRACT

Idiopathic pulmonary fibrosis (IPF) is a severe interstitial lung disease, and its pathogenesis remains unclear. In recent years, studies have shown that complement system activation plays an important role in the process of IPF. The inhibition of complement system activation provides a new approach for IPF treatment strategies. This article reviews the recent advances of complement system activation in the molecular mechanisms in the progress of IPF, and the potential therapeutic target in drug development, providing new perspectives for the prevention and treatment of IPF.

PMID:40300875 | DOI:10.3760/cma.j.cn112147-20241018-00621

Genome Biol. 2025 Apr 29;26(1):109. doi: 10.1186/s13059-025-03565-y.

ABSTRACT

Normalization of spatial transcriptomics data is challenging due to spatial association between region-specific library size and biology. We develop SpaNorm, the first spatially-aware normalization method that concurrently models library size effects and the underlying biology, segregates these effects, and thereby removes library size effects without removing biological information. Using 27 tissue samples from 6 datasets spanning 4 technological platforms, SpaNorm outperforms commonly used single-cell normalization approaches while retaining spatial domain information and detecting spatially variable genes. SpaNorm is versatile and works equally well for multicellular and subcellular spatial transcriptomics data with relatively robust performance under different segmentation methods.

PMID:40301877 | DOI:10.1186/s13059-025-03565-y

BMC Infect Dis. 2025 Apr 29;25(1):623. doi: 10.1186/s12879-025-10992-6.

ABSTRACT

BACKGROUND: The management of many chronic diseases requires a multidisciplinary and holistic approach. Long Covid is a recent, poorly understood disease with several symptoms. Most recommendations suggest a multidisciplinary approach. While there are a few programs aimed to the management of Long Covid, to our knowledge very few were assessed. The SPACO + study therefore aims to evaluate an innovative program which combines the methods used in therapeutic education and in personalized multifactorial intervention for management of Long Covid. Here, we present the protocol of our study, which aims to evaluate the effectiveness of an educational intervention in terms of changes in quality of life at 6 months in comparison with standard clinical practice in patients suffering from Long Covid.

METHODS: To achieve our objectives, we have planned to carry out a prospective, multicentre, two-arm randomized controlled trial with a convergent parallel mixed methods design. Two countries are involved in this study: France and Cameroon. The study concerns patients aged 18 and over, who have been infected with Covid-19. They must also be diagnosed as having Long Covid in accordance with the WHO definition. The number of subjects required for the study is 400 individuals. Participants will be randomly assigned to either the intervention or control group using a dynamic randomization process to ensure balanced group characteristics. The SPACO + program is an educative intervention with individual follow-up by a nurse dedicated to the program. The SPACO + program offers five workshops, two of which are compulsories. Patients take part in the other workshops according to their needs. The program includes an 8 - 10 weeks intervention period. Each session lasts two hours and includes breaks (pacing). The main outcome measure will be quality of life, evaluated through the SF-36. Primary and secondary outcomes, with few exceptions, are assessed before the intervention ("T0"), at 8 weeks ("T1" corresponding to the end of SPACO + program's session period) and then 3 months later ("T2").

DISCUSSION: If the SPACO + program is effective and accepted by professionals and patients, it could be disseminated in other regions to assess its transferability. The medico-economic evaluation will also make it possible to assess the benefits provided.

TRIAL REGISTRATION: This trial is registered under the number NCT05787366 (March 24, 2023). Protocol Version N°3.0 (May 31, 2024).

PMID:40301772 | DOI:10.1186/s12879-025-10992-6

Nat Biotechnol. 2025 Apr 29. doi: 10.1038/s41587-025-02660-6. Online ahead of print.

ABSTRACT

Microbiomes are complex communities of microorganisms that are essential for biochemical processes on Earth and for the health of humans, animals and plants. Many environmental and host-associated microbiomes are dominated by anaerobic microbes, some of which cannot tolerate oxygen. Anaerobic microbial communities have been extensively studied over the last 20 years using molecular techniques, especially next-generation sequencing. However, there is a renewed interest in microbial cultivation because isolates provide the basis for understanding the taxonomic and functional units of biodiversity, elucidating novel biochemical pathways and the mechanisms underlying microbe-microbe and microbe-host interactions and opening new avenues for biotechnological and clinical applications. In this Perspective, we present areas of research and applications that will benefit from advancement in anaerobic microbial cultivation. We highlight key technical and infrastructural hurdles associated with the development and deployment of sophisticated cultivation workflows. Improving the performance of cultivation techniques will set new trends in functional microbiome research in the coming years.

PMID:40301656 | DOI:10.1038/s41587-025-02660-6

Cell Death Differ. 2025 Apr 29. doi: 10.1038/s41418-025-01514-7. Online ahead of print.

ABSTRACT

Ferroptosis and apoptosis are widely considered to be independent cell death modalities. Ferroptotic cell death is a consequence of insufficient radical detoxification and progressive lipid peroxidation, which is counteracted by glutathione peroxidase-4 (GPX4). Apoptotic cell death can be triggered by a wide variety of stresses, including oxygen radicals, and can be suppressed by anti-apoptotic members of the BCL-2 protein family. Mitochondria are the main interaction site of BCL-2 family members and likewise a major source of oxygen radical stress. We therefore studied if ferroptosis and apoptosis might intersect and possibly interfere with one another. Indeed, cells dying from impaired GPX4 activity displayed hallmarks of both ferroptotic and apoptotic cell death, with the latter including (transient) membrane blebbing, submaximal cytochrome-c release and caspase activation. Targeting BCL-2, MCL-1 or BCL-XL with BH3-mimetics under conditions of moderate ferroptotic stress in many cases synergistically enhanced overall cell death and frequently skewed primarily ferroptotic into apoptotic outcomes. Surprisingly though, in other cases BH3-mimetics, most notably the BCL-XL inhibitor WEHI-539, counter-intuitively suppressed cell death and promoted cell survival following GPX4 inhibition. Further studies revealed that most BH3-mimetics possess previously undescribed antioxidant activities that counteract ferroptotic cell death at commonly employed concentration ranges. Our results therefore show that ferroptosis and apoptosis can intersect. We also show that combining ferroptotic stress with BH3-mimetics, context-dependently can either enhance and convert cell death outcomes between ferroptosis and apoptosis or can also suppress cell death by intrinsic antioxidant activities.

PMID:40301648 | DOI:10.1038/s41418-025-01514-7

Sci Rep. 2025 Apr 29;15(1):15049. doi: 10.1038/s41598-025-99425-7.

ABSTRACT

This study investigates the impact of irrigation water sources on the quality of olive oil from the Chemlal olive variety in the Hadjadj region, northeast of Mostaganem, Algeria, a coastal area known for its semi-arid climate and intensive olive cultivation. Olive trees (n = 50 per irrigation group) were irrigated with treated wastewater, spring water, and normal water, and the resulting oils were assessed for physicochemical properties, fatty acid composition, and bioactive compound profiles. Treated wastewater demonstrated distinct water quality characteristics, including elevated temperature (15.00 °C), chemical oxygen demand (COD: 58.38 mg/L), biochemical oxygen demand (BOD5: 29.00 mg/L), ammonium (15.60 mg/L), nitrite (2.55 mg/L), suspended solids (14.00 mg/L), pH (7.40), and conductivity (2.80 µS/cm), reflecting residual organic material and ionic content post-treatment. Heavy metal concentrations in all water sources were within permissible limits for irrigation and drinking purposes, affirming their safety for agricultural use. Olive oil from treated wastewater-irrigated trees exhibited superior quality parameters, including low acidity (1.99%), low peroxide value (6.8 meq O2/kg), enhanced oxidative stability, higher fat content (96.5%), and favorable saponification values. Fatty acid analysis revealed a higher oleic acid content (62.6 mg/kg), known for cardiovascular health benefits. Bioactive compound analysis indicated significantly elevated levels of α-tocopherol (180.25 mg/kg), squalene (7500.8 mg/kg), carotenoids (25.1 mg/kg), and polyphenols (604.76 mg GAE/kg), contributing to increased antioxidant capacity (63.50% DPPH inhibition, a measure of free radical scavenging) and lower lipid peroxidation (0.25 TBARS, an index of oxidative degradation), indicative of superior oxidative stability. Spring water-irrigated oils showed higher acidity, peroxide values, and linoleic acid concentrations, alongside notable antibacterial efficacy against Escherichia. coli, Pseudomonas. aeruginosa, and Staphylococcus. aureus. Oils from normal water irrigation were characterized by higher linolenic acid levels, providing a more balanced fatty acid profile. These findings underscore treated wastewater's potential to enhance olive oil's nutritional and functional qualities, particularly its antioxidant activity and stability, while highlighting the role of spring water in enhancing antibacterial properties despite slightly reduced antioxidant stability. These findings are relevant to water-scarce Mediterranean and arid regions, informing sustainable irrigation strategies in line with global climate-resilient agriculture policies.

PMID:40301569 | DOI:10.1038/s41598-025-99425-7

Sci Rep. 2025 Apr 29;15(1):15080. doi: 10.1038/s41598-025-99219-x.

ABSTRACT

Computational modeling and analysis of biomolecular network models annotated with omics data are emerging as a versatile tool for designing personalized therapies. Current endeavors aimed at employing in silico models towards personalized cancer therapeutics remain limited in providing all-in-one approach that ascertains actionable targets, re-positions FDA (Food and Drug Administration) approved drugs, furnishes quantitative cues on therapy responses such as efficacy and cytotoxic effect, and identifies novel drug combinations. Here we propose "CanSeer"-a methodology for developing personalized therapeutics. CanSeer employs patient-specific genetic alterations and RNA-seq data to annotate in silico models followed by dynamical network analyses towards assessment of treatment responses. To exemplify, three use cases involving paired samples, unpaired samples, and cancer samples only, of lung squamous cell carcinoma (LUSC) patients are provided. CanSeer reveals the effectiveness of repositioned drugs along with the identification of several novel LUSC treatment combinations including Afuresertib + Palbociclib, Dinaciclib + Trametinib, Afatinib + Oxaliplatin, Ulixertinib + Olaparib, etc.

PMID:40301468 | DOI:10.1038/s41598-025-99219-x

Cell Rep Methods. 2025 Apr 23:101030. doi: 10.1016/j.crmeth.2025.101030. Online ahead of print.

ABSTRACT

Quantification of the absolute microbial abundance in a human stool sample is crucial for a comprehensive understanding of the microbial ecosystem, but this information is lost upon metagenomic sequencing. While several methods exist to measure absolute microbial abundance, they are technically challenging and costly, presenting an opportunity for machine learning. Here, we observe a strong correlation between DNA concentration and the absolute number of 16S ribosomal RNA copies as measured by digital droplet PCR in clinical stool samples from individuals undergoing hematopoietic cell transplantation (BMT CTN 1801). Based on this correlation and additional measurements, we trained an accurate yet simple machine learning model for the prediction of absolute prokaryotic load, which showed exceptional prediction accuracy on an external cohort that includes people living with Parkinson's disease and healthy controls. We propose that, with further validation, this model has the potential to enable accurate absolute abundance estimation based on readily available sample measurements.

PMID:40300608 | DOI:10.1016/j.crmeth.2025.101030

Cell Rep Methods. 2025 Apr 23:101032. doi: 10.1016/j.crmeth.2025.101032. Online ahead of print.

ABSTRACT

Epigenomic profiling of the brain has largely been done on bulk tissues, limiting our understanding of cell type-specific epigenetic changes in disease states. Here, we introduce cell type-specific histone acetylation score (CHAS), a computational tool for inferring cell type-specific signatures in bulk brain H3K27ac profiles. We applied CHAS to >300 H3K27ac chromatin immunoprecipitation sequencing samples from studies of Alzheimer's disease, Parkinson's disease, autism spectrum disorder, schizophrenia, and bipolar disorder in bulk postmortem brain tissue. In addition to recapitulating known disease-associated shifts in cellular proportions, we identified cell type-specific biological insights into brain-disorder-associated regulatory variation. In most cases, genetic risk and epigenetic dysregulation targeted different cell types, suggesting independent mechanisms. For instance, genetic risk of Alzheimer's disease was exclusively enriched within microglia, while epigenetic dysregulation predominantly fell within oligodendrocyte-specific H3K27ac regions. In addition, reanalysis of the original datasets using CHAS enabled identification of biological pathways associated with each neurological and psychiatric disorder at cellular resolution.

PMID:40300607 | DOI:10.1016/j.crmeth.2025.101032

Cell Rep Methods. 2025 Apr 23:101031. doi: 10.1016/j.crmeth.2025.101031. Online ahead of print.

ABSTRACT

Biological tissues, as natural scattering media, inherently disrupt structural information, presenting significant challenges for optical imaging. Complex light propagation through tissue severely degrades image quality, limiting conventional fluorescence imaging techniques to superficial depths. Extracting meaningful information from random speckle patterns is, therefore, critical for deeper tissue imaging. In this study, we present RNP (robust non-negative principal matrix factorization), an approach that enables fluorescence microscopy under diverse scattering conditions. By integrating robust feature extraction with non-negativity constraints, RNP effectively addresses challenges posed by non-sparse signals and background interference in scattering tissue environments. The framework operates on a standard epi-fluorescence platform, eliminating the need for complex instrumentation or precise alignment. The results from imaging scattered cells and tissues demonstrate substantial improvements in robustness, field of view, depth of field, and image clarity. We anticipate that RNP will become a valuable tool for overcoming scattering challenges in fluorescence microscopy and driving advancements in biomedical research.

PMID:40300606 | DOI:10.1016/j.crmeth.2025.101031

Biosens Bioelectron. 2025 Apr 21;282:117475. doi: 10.1016/j.bios.2025.117475. Online ahead of print.

ABSTRACT

Extracellular vesicles (EVs) have emerged as promising biomarkers for various diseases. Encapsulating biomolecules reflective of their parental cells, EVs are readily accessible in bodily fluids. The prospect for minimally invasive, repeatable molecular testing has stimulated significant research; however, challenges persist in isolating EVs from complex biological matrices and characterizing their limited molecular cargo. Technical advances have been pursued to address these challenges, producing innovative EV-specific platforms. This review highlights recent technological developments, focusing on EV isolation and molecular detection methodologies. Furthermore, it explores the translation of these laboratory innovations to clinical applications through the analysis of patient samples, providing insights into the potential diagnostic and prognostic utility of EV-based technologies.

PMID:40300344 | DOI:10.1016/j.bios.2025.117475

IEEE J Biomed Health Inform. 2025 Apr 29;PP. doi: 10.1109/JBHI.2025.3565721. Online ahead of print.

ABSTRACT

As an effective and low-risk approach to identify new therapeutic pathways for existing drugs, drug repositioning has been extensively utilized to expedit drug discovery processes. However, current knowledge graph (KG)-based methodologies encounter several hurdles in this context. Firstly, most graph neural network (GNN)- based approaches fail to adequately capture the intricate relationships between drug-drug, drug-disease, or diseasedisease. Secondly, the subtle synergistic mechanisms between drugs and diseases remain underexplored. Lastly, the training of knowledge graph embedding (KGE) methods is susceptible to noise, leading to unstable model optimization. To address these challenges, we intruduce KRANE, a knowledge-driven and relation-aware synergistic learning method for drug repositioning. KRANE addresses these issues through three innovative modules. Firstly, we design a relation-aware feature extractor (RAFE), which utilizes the contextual triples attention scores in KG to effectively integrate drug-related knowledge and enhance the representation of complex relational features. Secondly, we adopt a synergistic feature reconstruction module as a decoder to extract synergistic heterogeneous feature interactions between drugs and diseases from entity and relation representations. Finally, we propose a knowledgeregulated loss function to mitigate the impact of noise on model training. Experiments conducted on three publicly available datasets demonstrate that KRANE significantly outperforms existing methods. The source code and datasets are available at https://github.com/qifen37/KRANE.

PMID:40299742 | DOI:10.1109/JBHI.2025.3565721

Pac Symp Biocomput. 2025;30:441-456. doi: 10.1142/9789819807024_0032.

ABSTRACT

Given the complexity and multifactorial nature of Alzheimer's disease, investigating potential drug-gene targets is imperative for developing effective therapies and advancing our understanding of the underlying mechanisms driving the disease. We present an explainable ML model that integrates the role and impact of gene interactions to drive the genomic variant feature selection. The model leverages both the Alzheimer's knowledge base and the Drug-Gene interaction database (DGIdb) to identify a list of biologically plausible novel gene-drug targets for further investigation. Model validation is performed on an ethnically diverse study sample obtained from the Alzheimer's Disease Sequencing Project (ADSP), a multi-ancestry multi-cohort genomic study. To mitigate population stratification and spurious associations from ML analysis, we implemented novel data curation methods. The study outcomes include a set of possible gene targets for further functional follow-up and drug repurposing.

PMID:40299608 | DOI:10.1142/9789819807024_0032

Pac Symp Biocomput. 2025;30:457-472. doi: 10.1142/9789819807024_0033.

ABSTRACT

Adverse drug responses (ADRs) result in over 7,000 deaths annually. Pharmacogenomic studies have shown that many ADRs are partially attributable to genetics. However, emerging data suggest that epigenetic mechanisms, such as DNA methylation (DNAm) also contribute to this variance. Understanding the impact of DNA methylation on drug response may minimize ADRs and improve the personalization of drug regimens. In this work, we identify DNA methylation sites that likely impact drug response phenotypes for anticoagulant and cardiometabolic drugs. We use instrumental variable analysis to integrate genome-wide association study (GWAS) summary statistics derived from electronic health records (EHRs) within the U.K. Biobank (UKBB) with methylation quantitative trait loci (mQTL) data from the Genetics of DNA Methylation Consortium (GoDMC). This approach allows us to achieve a robust sample size using the largest publicly available pharmacogenomic GWAS. For warfarin, we find 71 DNAm sites. Of those, 8 are near the gene VKORC1 and 48 are on chromosome 6 near the human leukocyte antigen (HLA) gene family. We also find 2 warfarin DNAm sites near the genes CYP2C9 and CYP2C19. For statins, we identify 17 DNAm sites. Eight are near the APOB gene, which encodes a carrier protein for low-density lipoprotein cholesterol (LDL-C). We find no novel significant epigenetic results for metformin.

PMID:40299609 | DOI:10.1142/9789819807024_0033

Pac Symp Biocomput. 2025;30:229-246. doi: 10.1142/9789819807024_0017.

ABSTRACT

Pharmacogenetics represents one of the most promising areas of precision medicine, with several guidelines for genetics-guided treatment ready for clinical use. Despite this, implementation has been slow, with few health systems incorporating the technology into their standard of care. One major barrier to uptake is the lack of education and awareness of pharmacogenetics among clinicians and patients. The introduction of large language models (LLMs) like GPT-4 has raised the possibility of medical chatbots that deliver timely information to clinicians, patients, and researchers with a simple interface. Although state-of-the-art LLMs have shown impressive performance at advanced tasks like medical licensing exams, in practice they still often provide false information, which is particularly hazardous in a clinical context. To quantify the extent of this issue, we developed a series of automated and expert-scored tests to evaluate the performance of chatbots in answering pharmacogenetics questions from the perspective of clinicians, patients, and researchers. We applied this benchmark to state-of-the-art LLMs and found that newer models like GPT-4o greatly outperform their predecessors, but still fall short of the standards required for clinical use. Our benchmark will be a valuable public resource for subsequent developments in this space as we work towards better clinical AI for pharmacogenetics.

PMID:40299593 | DOI:10.1142/9789819807024_0017

Int J Adolesc Med Health. 2025 May 1. doi: 10.1515/ijamh-2024-0192. Online ahead of print.

ABSTRACT

OBJECTIVES: With over 54,000 people affected, cystic fibrosis is one of the most common rare diseases in Europe. As life expectancy of this disease has steadily increased in recent years, the transition from pediatric to adult care has become a principal issue. This study aimed to identify facilitating and hindering factors in the transitional care of cystic fibrosis patients in order to derive indications for improving care.

METHODS: A qualitative systematized review was conducted in May 2024 with a systematic search carried out in MEDLINE, CINAHL and Livivo, including European studies from 2009 to 2024. The studies' quality was assessed using the Critical Appraisal Skills Programme checklist for qualitative studies. Thematic analysis was applied for analyzing the data to identify categories.

RESULTS: Nine studies met the inclusion criteria. Their quality can be rated as medium to high. Parental support, commitment and social support were identified as beneficial factors. Preparation for the transition, appropriate communication and continuous follow-ups at the adult center also contributed to a continuous transition. However, the parents' changing roles, fears and the usual treatment in pediatrics were obstacles. The adjustment to the adult center and structural problems presented further barriers to transition.

CONCLUSIONS: Various factors were identified to influence the transition process in cystic fibrosis, with consistency across the studies. In practice, comprehensive care is required, focused on the patients' needs, with more information provided and enhanced collaboration among stakeholders. Further research regarding the long-term effects of transition and the utilization of structured transition programs is needed.

PMID:40300192 | DOI:10.1515/ijamh-2024-0192