Science. 2025 Feb 21;387(6736):880-885. doi: 10.1126/science.ads7942. Epub 2025 Feb 20.

ABSTRACT

The vision of robotic materials-cohesive collectives of robotic units that can arrange into virtually any form with any physical properties-has long intrigued both science and fiction. Yet, this vision requires a fundamental physical challenge to be overcome: The collective must be strong, to support loads, yet flow, to take new forms. We achieve this in a material-like robotic collective by modulating the interunit tangential forces to control topological rearrangements of units within a tightly packed structure. This allows local control of rigidity transitions between solid and fluid-like states in the collective and enables spatiotemporal control of shape and strength. We demonstrate structure-forming and healing and show the collective supporting 700 newtons (500 times the weight of a robot) before "melting" under its own weight.

PMID:39977492 | DOI:10.1126/science.ads7942

Proc Natl Acad Sci U S A. 2025 Feb 25;122(8):e2420164122. doi: 10.1073/pnas.2420164122. Epub 2025 Feb 20.

ABSTRACT

Biosynthetic gene clusters (BGCs) are sets of often heterologous genes that are genetically and functionally linked. Among eukaryotes, BGCs are most common in plants and fungi and ensure the coexpression of the different enzymes coordinating the biosynthesis of specialized metabolites. Here, we report the identification of a withanolide BGC in Physalis grisea (ground-cherry), a member of the nightshade family (Solanaceae). A combination of transcriptomic, epigenomic, and metabolic analyses revealed that, following a duplication event, this BGC evolved two tissue-specifically expressed subclusters, containing several pairs of paralogs that contribute to related but distinct biochemical processes; this subfunctionalization is tightly associated with epigenetic features and the local chromatin environment. The two subclusters appear strictly isolated from each other at the structural chromatin level, each forming a highly self-interacting chromatin domain with tissue-dependent levels of condensation. This correlates with gene expression in either above- or below-ground tissue, thus spatially separating the production of different withanolide compounds. By comparative phylogenomics, we show that the withanolide BGC most likely evolved before the diversification of the Solanaceae family and underwent lineage-specific diversifications and losses. The tissue-specific subfunctionalization is common to species of the Physalideae tribe but distinct from other, independent duplication events outside of this clade. In sum, our study reports on an instance of an epigenetically modulated subfunctionalization within a BGC and sheds light on the biosynthesis of withanolides, a highly diverse group of steroidal triterpenoids important in plant defense and amenable to pharmaceutical applications due to their anti-inflammatory, antibiotic, and anticancer properties.

PMID:39977312 | DOI:10.1073/pnas.2420164122

J Infect Dev Ctries. 2025 Jan 31;19(1):58-66. doi: 10.3855/jidc.19554.

ABSTRACT

INTRODUCTION: A prescribing cascade occurs when new medications are prescribed to address an adverse drug reaction (ADR) associated with the preceding use of a medication, which may be mistaken as the onset of a novel disease or condition. The aim of this study was to evaluate the perceptions of hospital pharmacists regarding roles in preventing and minimizing prescribing cascades.

METHODOLOGY: A qualitative, semi-structured interview, followed by a quantitative, questionnaire-based study, was carried out at the Shifa International Hospital (SIH; Islamabad, Pakistan). Discharge summaries of patients aged ≥ 60 years were collected to assess the prevalence of polypharmacy at SIH.

RESULTS: Discharge summaries of n = 350 patients were collected; 60.2% (n = 211) had comorbid conditions, and the co-occurrence of diabetes and hypertension were the most common. 37.8% (n = 132) were taking 8 or more medications. Eight (n = 8) hospital pharmacists participated in the qualitative study, and 4 major themes were identified in their perceptions regarding prescribing cascades. Fifty-two (n = 52) pharmacists were recruited in the quantitative phase. 86.5% (n = 45) of the participants reported long standing illness/chronic conditions; 67.3% (n = 35) noted the presence of comorbidities as a high risk, while 90.3% (n = 47) noted multiple prescribers, and 75.0% (n = 39) identified the ageing population as important risks factors for polypharmacy.

CONCLUSIONS: The current research may inform the role and responsibilities of hospital pharmacists in outpatient and inpatient departments, and in interprofessional care teams, in preventing and minimizing prescribing cascades.

PMID:39977468 | DOI:10.3855/jidc.19554

Expert Opin Drug Saf. 2025 Feb 20:1-9. doi: 10.1080/14740338.2025.2468861. Online ahead of print.

ABSTRACT

BACKGROUND: Drug-induced hypokalemia is often associated with adverse clinical outcomes, and unfortunately, the inability to fully understand the drugs that cause hypokalemia puts us in a passive position. This study applies pharmacovigilance data to present a panorama of suspected medications associated with hyperkalemia.

RESEARCH DESIGN AND METHODS: This study used disproportionality analysis to mine adverse events in OpenFDA, identified all suspected drugs that caused hypokalemia, and coded and classified the suspected drugs according to the Anatomical Therapeutic Chemical (ATC) classification system.

RESULTS: There are 19755 reports related to drug-induced hypokalemia. The majority of individuals with hypokalemia are females, with a concentrated age range of 65 to 84 years old. After the occurrence of hypokalemia, 8.02% died due to hypokalemia. This study identified 1141 suspected drugs, and among the top 50 drugs, 32 drugs did not include hypokalemia in their instructions. All suspected drugs can be categorized into 73 subgroups according to the ATC classification system.

CONCLUSIONS: By mining the OpenFDA database, we have identified all suspected drugs that cause hypokalemia and conducted a comprehensive evaluation. The instructions for most of the suspected drugs do not focus on hypokalemia. When the treatment regimen includes other drugs that can directly/indirectly cause a decrease in blood potassium, we recommend actively monitoring blood potassium when using suspected drugs.

PMID:39977281 | DOI:10.1080/14740338.2025.2468861

Microbiology (Reading). 2025 Feb;171(2). doi: 10.1099/mic.0.001536.

ABSTRACT

Obtaining sputum samples from people with cystic fibrosis (pwCF) for microbiology has become challenging due to the positive clinical effects of the cystic fibrosis transmembrane conductance regulator modulator therapy, elexacaftor-tezacaftor-ivacaftor (ETI). Although ETI improves lung function and reduces sputum production, recent data shows that bacterial pathogens persist, making continued monitoring of infection important. As an alternative to sputum sampling, this study developed a non-invasive technique called 'Cough Breath' (CB) to identify volatile organic compounds (VOCs) in exhaled breath condensate (EBC) and link them to cystic fibrosis (CF) bacterial pathogens using purge and trap GC-MS. The CB culturing approach was able to isolate pathogens from expectorated particulates simultaneously with EBC collection; however, culturing positivity was low, with 6% of samples collected (n=47) positive for either Pseudomonas aeruginosa or Staphylococcus aureus. From EBC, we identified VOCs matching those uniquely produced by P. aeruginosa (7), S. aureus (12), Achromobacter xylosoxidans (8) and Granulicatella adiacens (2); however, the overall detection rate was also low. Expanding to VOCs produced across multiple pathogens identified 30 frequently detected in the EBC of pwCF, including 2,3-pentanedione, propyl pyruvate, oxalic acid diallyl ester, methyl isobutyl ketone, methyl nitrate, 2-propenal, acetonitrile, acetoin and 2,3-butanedione. Comparing isolate volatilomes and EBC samples from the same pwCF enhanced detection rates with key VOCs, such as 2,3-pentanedione (86%) and propyl pyruvate (83%), in P. aeruginosa isolates. Further investigation showed that VOC production differed across strains and at different growth phases, creating variability that may explain the overall low EBC detection rate. Although this study successfully cultured CF pathogens from cough particulates and matched their unique VOCs in EBC samples, our results indicate that microbial volatiles more generally indicative of infection, such as 2,3-pentanedione, may have the most utility in aiding diagnostics in pwCF on ETI who have reduced sputum production in the clinic.

PMID:39976612 | DOI:10.1099/mic.0.001536

Int J Comput Assist Radiol Surg. 2025 Feb 20. doi: 10.1007/s11548-025-03335-y. Online ahead of print.

ABSTRACT

PURPOSE: While deep learning methods have shown great promise in improving the effectiveness of prostate cancer (PCa) diagnosis by detecting suspicious lesions from trans-rectal ultrasound (TRUS), they must overcome multiple simultaneous challenges. There is high heterogeneity in tissue appearance, significant class imbalance in favor of benign examples, and scarcity in the number and quality of ground truth annotations available to train models. Failure to address even a single one of these problems can result in unacceptable clinical outcomes.

METHODS: We propose TRUSWorthy, a carefully designed, tuned, and integrated system for reliable PCa detection. Our pipeline integrates self-supervised learning, multiple-instance learning aggregation using transformers, random-undersampled boosting and ensembling: These address label scarcity, weak labels, class imbalance, and overconfidence, respectively. We train and rigorously evaluate our method using a large, multi-center dataset of micro-ultrasound data.

RESULTS: Our method outperforms previous state-of-the-art deep learning methods in terms of accuracy and uncertainty calibration, with AUROC and balanced accuracy scores of 79.9% and 71.5%, respectively. On the top 20% of predictions with the highest confidence, we can achieve a balanced accuracy of up to 91%.

CONCLUSION: The success of TRUSWorthy demonstrates the potential of integrated deep learning solutions to meet clinical needs in a highly challenging deployment setting, and is a significant step toward creating a trustworthy system for computer-assisted PCa diagnosis.

PMID:39976857 | DOI:10.1007/s11548-025-03335-y

Eur J Trauma Emerg Surg. 2025 Feb 20;51(1):115. doi: 10.1007/s00068-025-02779-w.

ABSTRACT

OBJECTIVES: Pediatric elbow fractures are a common injury among children. Recent advancements in artificial intelligence (AI), particularly deep learning (DL), have shown promise in diagnosing these fractures. This study systematically evaluated the performance of DL models in detecting pediatric elbow fractures.

MATERIALS AND METHODS: A comprehensive search was conducted in PubMed (Medline), EMBASE, and IEEE Xplore for studies published up to October 20, 2023. Studies employing DL models for detecting elbow fractures in patients aged 0 to 16 years were included. Key performance metrics, including sensitivity, specificity, and area under the curve (AUC), were extracted. The study was registered in PROSPERO (ID: CRD42023470558).

RESULTS: The search identified 22 studies, of which six met the inclusion criteria for the meta-analysis. The pooled sensitivity of DL models for pediatric elbow fracture detection was 0.93 (95% CI: 0.91-0.96). Specificity values ranged from 0.84 to 0.92 across studies, with a pooled estimate of 0.89 (95% CI: 0.85-0.92). The AUC ranged from 0.91 to 0.99, with a pooled estimate of 0.95 (95% CI: 0.93-0.97). Further analysis highlighted the impact of preprocessing techniques and the choice of model backbone architecture on performance.

CONCLUSION: DL models demonstrate exceptional accuracy in detecting pediatric elbow fractures. For optimal performance, we recommend leveraging backbone architectures like ResNet, combined with manual preprocessing supervised by radiology and orthopedic experts.

PMID:39976732 | DOI:10.1007/s00068-025-02779-w

Eur J Nucl Med Mol Imaging. 2025 Feb 20. doi: 10.1007/s00259-025-07145-x. Online ahead of print.

ABSTRACT

BACKGROUND: Myocardial perfusion imaging (MPI) using single-photon emission computed tomography (SPECT) is a well-established modality for noninvasive diagnostic assessment of coronary artery disease (CAD). However, the time-consuming and experience-dependent visual interpretation of SPECT images remains a limitation in the clinic.

PURPOSE: We aimed to develop advanced models to diagnose CAD using different supervised and semi-supervised deep learning (DL) algorithms and training strategies, including transfer learning and data augmentation, with SPECT-MPI and invasive coronary angiography (ICA) as standard of reference.

MATERIALS AND METHODS: A total of 940 patients who underwent SPECT-MPI were enrolled (281 patients included ICA). Quantitative perfusion SPECT (QPS) was used to extract polar maps of rest and stress states. We defined two different tasks, including (1) Automated CAD diagnosis with expert reader (ER) assessment of SPECT-MPI as reference, and (2) CAD diagnosis from SPECT-MPI based on reference ICA reports. In task 2, we used 6 strategies for training DL models. We implemented 13 different DL models along with 4 input types with and without data augmentation (WAug and WoAug) to train, validate, and test the DL models (728 models). One hundred patients with ICA as standard of reference (the same patients in task 1) were used to evaluate models per vessel and per patient. Metrics, such as the area under the receiver operating characteristics curve (AUC), accuracy, sensitivity, specificity, precision, and balanced accuracy were reported. DeLong and pairwise Wilcoxon rank sum tests were respectively used to compare models and strategies after 1000 bootstraps on the test data for all models. We also compared the performance of our best DL model to ER's diagnosis.

RESULTS: In task 1, DenseNet201 Late Fusion (AUC = 0.89) and ResNet152V2 Late Fusion (AUC = 0.83) models outperformed other models in per-vessel and per-patient analyses, respectively. In task 2, the best models for CAD prediction based on ICA were Strategy 3 (a combination of ER- and ICA-based diagnosis in train data), WoAug InceptionResNetV2 EarlyFusion (AUC = 0.71), and Strategy 5 (semi-supervised approach) WoAug ResNet152V2 EarlyFusion (AUC = 0.77) in per-vessel and per-patient analyses, respectively. Moreover, saliency maps showed that models could be helpful for focusing on relevant spots for decision making.

CONCLUSION: Our study confirmed the potential of DL-based analysis of SPECT-MPI polar maps in CAD diagnosis. In the automation of ER-based diagnosis, models' performance was promising showing accuracy close to expert-level analysis. It demonstrated that using different strategies of data combination, such as including those with and without ICA, along with different training methods, like semi-supervised learning, can increase the performance of DL models. The proposed DL models could be coupled with computer-aided diagnosis systems and be used as an assistant to nuclear medicine physicians to improve their diagnosis and reporting, but only in the LAD territory.

CLINICAL TRIAL NUMBER: Not applicable.

PMID:39976703 | DOI:10.1007/s00259-025-07145-x

J Appl Clin Med Phys. 2025 Feb 20:e70031. doi: 10.1002/acm2.70031. Online ahead of print.

ABSTRACT

PURPOSE: To compare image quality and clinical utility of a T2-weighted (T2W) 3-dimensional (3D) fast spin echo (FSE) sequence using deep learning reconstruction (DLR) versus conventional reconstruction for rectal magnetic resonance imaging (MRI).

METHODS: The study included 50 patients with rectal cancer who underwent rectal MRI consecutively between July 7, 2020 and January 20, 2021 using a T2W 3D FSE sequence with DLR and conventional reconstruction. Three radiologists reviewed the two sets of images, scoring overall SNR, motion artifacts, and overall image quality on a 3-point scale and indicating clinical preference for DLR or conventional reconstruction based on those three criteria as well as image characterization of bowel wall layer definition, tumor invasion of muscularis propria, residual disease, fibrosis, nodal margin, and extramural venous invasion.

RESULTS: Image quality was rated as moderate or good for both DLR and conventional reconstruction for most cases. DLR was preferred over conventional reconstruction in all of the categories except for bowel wall layer definition.

CONCLUSION: Both conventional reconstruction and DLR provide acceptable image quality for T2W 3D FSE imaging of rectal cancer. DLR was clinically preferred over conventional reconstruction in almost all categories.

PMID:39976552 | DOI:10.1002/acm2.70031

Med Phys. 2025 Feb 20. doi: 10.1002/mp.17696. Online ahead of print.

ABSTRACT

BACKGROUND: Deformable medical image registration aims to align image pairs with local differences, improving the accuracy of medical analyses and assisting various diagnostic scenarios.

PURPOSE: We aim to overcome these challenges: Deep learning-based registration approaches have greatly enhanced registration speed and accuracy by continuously improving registration networks and processes. However, the lack of extensive medical datasets limits the complexity of registration models. Optimizing registration networks within a fixed dataset often leads to overfitting, hindering further accuracy improvements and reducing generalization capabilities.

METHODS: We explore the application of the foundational model DINOv2 to registration tasks, leveraging its prior knowledge to support learning-based unsupervised registration networks and overcome network bottlenecks to improve accuracy. We investigate three modes of DINOv2-assisted registration, including direct registration architecture, enhanced architecture, and refined architecture. Additionally, we study the applicability of three feature aggregation methods-convolutional interaction, direct fusion, and cross-attention-within the proposed DINOv2-based registration frameworks.

RESULTS: We conducted extensive experiments on the IXI and OASIS public datasets, demonstrating that the enhanced and refined architectures notably improve registration accuracy, reduce data dependency, and maintain strong generalization capabilities.

CONCLUSION: This study offers novel approaches for applying foundational models to deformable image registration tasks.

PMID:39976314 | DOI:10.1002/mp.17696

Stat Med. 2025 Feb 28;44(5):e70020. doi: 10.1002/sim.70020.

ABSTRACT

Freezing of Gait (FOG) is a prevalent symptom in advanced Parkinson's Disease (PD), characterized by intermittent transitions between normal gait and freezing episodes. This study introduces a novel graph-theoretic approach to detect FOG from video data of PD patients. We construct a sequence of pose graphs that represent the spatial relations and temporal progression of a patient's posture over time. Each graph node corresponds to an estimated joint position, while the edges reflect the anatomical connections and their proximity. We propose a hypothesis testing procedure that deploys the Fréchet statistics to identify break points in time between regular gait and FOG episodes, where we model the central tendency and dispersion of the pose graphs in the presentation of graph Laplacian matrices by computing their Fréchet mean and variance. We implement binary segmentation and incremental computation in our algorithm for efficient calculation. The proposed framework is validated on two datasets, Kinect3D and AlphaPose, demonstrating its effectiveness in detecting FOG from video data. The proposed approach that extracts matrix features is distinct from the prevailing pixel-based deep learning methods. It provides a new perspective on feature extraction for FOG detection and potentially contributes to improved diagnosis and treatment of PD.

PMID:39976295 | DOI:10.1002/sim.70020

Crit Rev Immunol. 2025;45(2):77-89. doi: 10.1615/CritRevImmunol.2025056518.

ABSTRACT

BACKGROUND: Sarcoidosis is a complex inflammatory disease of unknown etiology affecting mostly the lungs and poses a significant diagnostic challenge, particularly in regions where tuberculosis (TB) is endemic. The diagnostic complexity intensifies due to shared clinical and radiological features between sarcoidosis and TB, as well as similarities with idiopathic pulmonary fibrosis (IPF) in cases that progress to pulmonary fibrosis. Accurately distinguishing between these diseases is critical for timely and effective patient management.

OBJECTIVE: This study breaks new ground by evaluating the diagnostic power of the bronchoalveolar lavage (BAL) CD4/ CD8 ratio, along with key activation and memory markers to differentiate sarcoidosis from TB, IPF, and other-interstitial lung diseases (ILDs).

METHODS: A cohort of 68 patients with ILDs, including sarcoidosis (n = 37), TB (n = 19), IPF (n = 6), and Other-ILDs (n = 6) were assessed. The CD4/CD8 ratio and a panel of activation and memory markers were analyzed through flow cytometry.

RESULTS: Sarcoidosis exhibited a significantly higher CD4/CD8 ratio compared to those with TB, IPF, and Other-ILDs. An optimal cutoff value of 3.7 for the CD4/CD8 ratio in sarcoidosis with an area under the ROC curve (AUC) of 0.7%, had a specificity of 96.8%, and a sensitivity of 43.2%. In addition, a significant difference was detected in CD38, CD45RA, CD45RO, and CD62L expression.

CONCLUSION: Combining the CD4/CD8 ratio (> 3.7) with the expression of CD38, CD62L, and memory markers is a promising new tool for the differential diagnosis of sarcoidosis.

PMID:39976519 | DOI:10.1615/CritRevImmunol.2025056518

Elife. 2025 Feb 20;13:RP99352. doi: 10.7554/eLife.99352.

ABSTRACT

Populations can adapt to stressful environments through changes in gene expression. However, the fitness effect of gene expression in mediating stress response and adaptation remains largely unexplored. Here, we use an integrative field dataset obtained from 780 plants of Oryza sativa ssp. indica (rice) grown in a field experiment under normal or moderate salt stress conditions to examine selection and evolution of gene expression variation under salinity stress conditions. We find that salinity stress induces increased selective pressure on gene expression. Further, we show that trans-eQTLs rather than cis-eQTLs are primarily associated with rice's gene expression under salinity stress, potentially via a few master-regulators. Importantly, and contrary to the expectations, we find that cis-trans reinforcement is more common than cis-trans compensation which may be reflective of rice diversification subsequent to domestication. We further identify genetic fixation as the likely mechanism underlying this compensation/reinforcement. Additionally, we show that cis- and trans-eQTLs are under balancing and purifying selection, respectively, giving us insights into the evolutionary dynamics of gene expression variation. By examining genomic, transcriptomic, and phenotypic variation across a rice population, we gain insights into the molecular and genetic landscape underlying adaptive salinity stress responses, which is relevant for other crops and other stresses.

PMID:39976326 | DOI:10.7554/eLife.99352

J Extracell Vesicles. 2025 Feb;14(2):e70046. doi: 10.1002/jev2.70046.

ABSTRACT

Up-regulation of Centrosomal Protein 55 (CEP55) in cancer cells increases malignancy, and the protein can be transferred via exosomes. However, the mechanism of how CEP55 is delivered to exosomes is unknown. In this study, we addressed this issue and analysed trafficking of EGFP-CEP55 from early to late endosomes by using high-resolution microscopy. Our data show that endogenous as well as EGFP-CEP55 appeared as dot-like structures in cancer cells. However, we did not find an internalization of CEP55 into early Rab5- and late Rab7-positive endosomes but only into secretory late CD63-positive endosomes. In addition, an association of the CEP55 dots with the endoplasmic reticulum and with ALG-2-interacting protein X (Alix) dots was detected. Moreover, mutation of the CEP55-Alix interaction site strongly reduced the formation of CEP55 dots as well as CEP55 localization in extracellular vesicles. In summary, our data indicate that delivery of CEP55 into exosomes does not occur by the canonical early-to-late endosome pathway but by Alix-mediated recruitment to secretory late secretory CD63 endosomes.

PMID:39976236 | DOI:10.1002/jev2.70046

Neurol Ther. 2025 Feb 20. doi: 10.1007/s40120-024-00697-4. Online ahead of print.

ABSTRACT

INTRODUCTION: Efficacy/tolerability of adjunctive brivaracetam (BRV) for focal-onset seizures (FOS) in patients aged ≥ 16 years was established in randomized controlled trials. This study aimed to evaluate the effectiveness of adjunctive BRV in patients (≥ 16 years) with FOS with/without focal to bilateral tonic-clonic seizures in daily clinical practice.

METHODS: A 12-month, prospective, real-world, noninterventional study in nine European countries (EP0077/NCT02687711). BRV was prescribed per clinical practice and European Summary of Product Characteristics. Eligible patients had never received BRV before inclusion. Treating physicians made the decision to prescribe BRV, independently of study participation. Primary effectiveness outcome: BRV retention rate at 12 months; secondary effectiveness outcomes: 50% responder rate, seizure freedom.

RESULTS: A total of 544 patients received ≥ 1 BRV dose (mean age: 43.6 years; 52.8% female; mean time since diagnosis: 22.7 years). Patients had a mean of 7.3 lifetime antiseizure medications (ASMs) and median of 3.7 FOS/28 days during 3-month retrospective baseline. Median total ASM drug load (including BRV) was 3.0 at BRV initiation (n = 539) and 3.3 at study end (n = 314). At 12 months, 57.7% of 541 patients remained on BRV, 60.4% of 230 were responders (≥ 50% seizure reduction since baseline), and 13.8% of 269 were seizure-free since BRV initiation. Historical levetiracetam use appeared not to impact retention rate (56.6% of 320 and 59.3% of 221 patients with and without historical levetiracetam use, respectively). 36.0% of 544 patients had drug-related treatment-emergent adverse events (TEAEs), mostly (≥ 5% of patients) drug ineffective (11.4%) and seizure (6.3%). The three most common drug-related TEAEs leading to permanent BRV discontinuation (of 544 patients) were drug ineffective (10.1%), seizure (5.1%), and behavior disorder (3.3%).

CONCLUSIONS: Adjunctive BRV was effective in clinical practice in patients with predominantly difficult-to-treat FOS, as shown by BRV retention rate of 57.7% at 12 months, which is in line with real-world retention rates for other new-generation ASMs.

PMID:39976891 | DOI:10.1007/s40120-024-00697-4

J Neuromuscul Dis. 2024 Dec 20:22143602241296226. doi: 10.1177/22143602241296226. Online ahead of print.

ABSTRACT

GNE myopathy is an autosomal recessive hereditary muscle disorder that has the following clinical characteristics: develops in early adulthood, gradually progresses from the distal muscles, and is relatively sparing of quadriceps until the advanced stages of the disease. With further progression, patients become non-ambulatory and need a wheelchair. There is growing concern about extra-muscular presentations such as thrombocytopenia, respiratory dysfunction, and sleep apnea syndrome. Pathologically, rimmed vacuoles and tubulofilamentous inclusions are observed in affected muscles. The cause of the disease is thought to be a sialic acid deficiency due to mutations of the GNE gene required for in vivo sialic acid biosynthesis. Sialic acid supplementation to a presymptomatic GNE myopathy mouse model was effective in preventing the development of the disease. Several clinical studies have been conducted to evaluate the safety and efficacy of sialic acid supplementation in humans. Based on the favorable results of these studies, an extended-release aceneuramic acid formulation was approved for treatment of GNE myopathy in Japan in March 2024. It is anticipated that it will be a significant step in the development of an effective treatment for GNE myopathy and other ultra-orphan diseases.

PMID:39973407 | DOI:10.1177/22143602241296226

medRxiv [Preprint]. 2025 Feb 2:2025.01.31.25321503. doi: 10.1101/2025.01.31.25321503.

ABSTRACT

We developed a simulated process to show a software implementation to facilitate an approach to integrate the Informed Consent Ontology, a reference ontology of informed consent information, to express implicit description and implement conceptual permission from informed consent life cycle. An early study introduced an experimental method to use Semantic Web Rule Language (SWRL) to describe and represent permissions to computational deduce more information from the Informed Consent Ontology (ICO), demonstrated by the use of the All of Us informed consent documents. We show how incomplete information in informed consent documents can be elucidated using a computational model of permissions toward health information technology that integrates ontologies. Future goals entail applying our computational approach for specific sub-domains of the informed consent life cycle, specifically for vaccine informed consent.

PMID:39974098 | PMC:PMC11838618 | DOI:10.1101/2025.01.31.25321503

Eur J Gastroenterol Hepatol. 2025 Jan 21. doi: 10.1097/MEG.0000000000002917. Online ahead of print.

ABSTRACT

BACKGROUND: Cystic fibrosis-related liver disease (CFRLD) is a health problem that can affect as many as 30-40% of cystic fibrosis patients by the age of 12 years. We studied the epidemiology of CFRLD thanks to the first exclusively pediatric CFRLD patient registry to date.

METHODS: Descriptive cross-sectional study. Information from medical records from January 2018 to December 2020 is collected. CFRLD was classified according to the European Society of Paediatric Gastroenterology, Hepatology and Nutrition 2017 criteria.

RESULTS: Data were collected from 168 pediatric patients diagnosed with CFRLD (90.5% liver involvement without cirrhosis and 8.5% multinodular cirrhosis).

CONCLUSION: In this national registry, including exclusively pediatric population, liver disease is diagnosed around 7 years of age. Liver involvement without cirrhosis is the most frequent finding among our patients but about 9% of the patients already had cirrhosis. CFRLD is one of the challenges faced by pediatric gastroenterologists in the future and national registries give us the opportunity to further study and broaden our knowledge.

PMID:39976013 | DOI:10.1097/MEG.0000000000002917

bioRxiv [Preprint]. 2025 Feb 8:2025.02.03.636268. doi: 10.1101/2025.02.03.636268.

ABSTRACT

Constipation causes significant morbidity in Cystic Fibrosis (CF) patients. Using CF patient (F508del) derived ex vivo ileal and distal colonic/rectal enteroids as a model and the Forskolin Induced Swelling Assay (FIS), we compared CFTR mediated fluid secretion in human enterocytes across the crypt-villus axis. CFTR expression and FIS decreased as enterocytes differentiated from crypt to become partially differentiated and then mature villus cells . While there was no FIS response in undifferentiated (crypt enterocytes) F508del-CF enteroids, partially differentiated F508del-CF enteroids had a swelling response to forskolin (cAMP) and linaclotide (cGMP) which was ∼48%, and ∼67% of the response in healthy enteroids, respectively and was prevented by a CFTR inhibitor. Also, linaclotide and a general PDE inhibitor independently enhanced combined CFTR-modulator-induced FIS response from partially differentiated F508del-CF enteroids. These findings demonstrate that partially differentiated ileal and distal colonic F508del-CFTR enteroids can be stimulated to secrete fluid by cAMP and cGMP.

PMID:39975121 | PMC:PMC11838475 | DOI:10.1101/2025.02.03.636268

bioRxiv [Preprint]. 2025 Jan 27:2025.01.24.634747. doi: 10.1101/2025.01.24.634747.

ABSTRACT

Single-cell RNA sequencing (scRNA-seq) studies identified a novel subpopulation of epithelial cells along the rostrocaudal axis of human intestine specifically marked by bestrophin 4 (BEST4) that are enriched for genes regulating pH, GPCR acid-sensing receptors, satiety, cGMP signaling, HCO3 - secretion, ion transport, neuropeptides, and paracrine hormones. Interestingly, BEST4+ cells in the proximal small intestine express CFTR but have not been linked to the previously described CFTR High Expresser Cell (CHE) subpopulation in rat and human intestine. ScRNA-seq studies in rat jejunum identified CHEs and a gene expression profile consistent with human small intestinal BEST4+ and neuropod cells. Protein immunolocalization confirmed that CHEs express CFTR, BEST4, neuropod proteins, high levels of intracellular uroguanylin (UGN), guanylyl cyclase-C (GC-C), and the proton channel otopetrin 2 (OTOP2), and display long basal processes connecting to neurons. OTOP2, GC-C, and CFTR traffic robustly into the apical domain of CHEs in response to acidic luminal conditions, indicating their roles in luminal pH regulation. In the ΔF508 cystic fibrosis (CF) rat jejunum, the loss of apical CFTR did not affect BEST4 protein expression in CHEs. However, there was an increased abundance of CHE cells in the ΔF508 rat jejunum compared to wild-type animals. Furthermore, ΔF508 rat CHEs expressed higher levels of GC-C at the apical domain compared to wild-type. These data implicate CHEs in intestinal CF disease pathogenesis.

NEW & NOTEWORTHY: This is the first study to identify CFTR High Expresser cells in the rat small intestine as neuropod cells capable of sensing and responding to luminal pH. This study also provides the first characterization of CFTR and relevant mRNA and proteins in CHEs in CF rat models that provide insights into the significance of CHEs to CF intestinal disease.

PMID:39974899 | PMC:PMC11838207 | DOI:10.1101/2025.01.24.634747