J Chem Inf Model. 2025 Apr 14. doi: 10.1021/acs.jcim.4c02345. Online ahead of print.

ABSTRACT

The development of new materials is a time-consuming and resource-intensive process. Deep learning has emerged as a promising approach to accelerate this process. However, accurately predicting crystal structures using deep learning remains a significant challenge due to the complex, high-dimensional nature of atomic interactions and the scarcity of comprehensive training data that captures the full diversity of possible crystal configurations. This work developed a neural network model based on a data set comprising thousands of crystallographic information files from existing crystal structure databases. The model incorporates a self-attention mechanism to enhance prediction accuracy by learning and extracting both local and global features of three-dimensional structures, treating the atoms in each crystal as point sets. This approach enables effective semantic segmentation and accurate unit cell prediction. Experimental results demonstrate that for unit cells containing up to 500 atoms, the model achieves a structure prediction accuracy of 89.78%.

PMID:40228012 | DOI:10.1021/acs.jcim.4c02345

J Vis Exp. 2025 Mar 28;(217). doi: 10.3791/67766.

ABSTRACT

Finger gestures are a critical element in human communication, and as such, finger gesture recognition is widely studied as a human-computer interface for state-of-the-art prosthetics and optimized rehabilitation. Surface electromyography (sEMG), in conjunction with deep learning methods, is considered a promising method in this domain. However, current methods often rely on cumbersome recording setups and the identification of static hand positions, limiting their effectiveness in real-world applications. The protocol we report here presents an advanced approach combining a wearable surface EMG and finger tracking system to capture comprehensive data during dynamic hand movements. The method records muscle activity from soft printed electrode arrays (16 electrodes) placed on the forearm as subjects perform gestures in different hand positions and during movement. Visual instructions prompt subjects to perform specific gestures while EMG and finger positions are recorded. The integration of synchronized EMG recordings and finger tracking data enables comprehensive analysis of muscle activity patterns and corresponding gestures. The reported approach demonstrates the potential of combining EMG and visual tracking technologies as an important resource for developing intuitive and responsive gesture recognition systems with applications in prosthetics, rehabilitation, and interactive technologies. This protocol aims to guide researchers and practitioners, fostering further innovation and application of gesture recognition in dynamic and real-world scenarios.

PMID:40227996 | DOI:10.3791/67766

IEEE Trans Med Imaging. 2025 Apr 14;PP. doi: 10.1109/TMI.2025.3558861. Online ahead of print.

ABSTRACT

Deep learning has demonstrated exceptional performance in medical image analysis, but its effectiveness degrades significantly when applied to different medical centers due to domain shifts. Lesion detection, a critical task in medical imaging, is particularly impacted by this challenge due to the diversity and complexity of lesions, which can arise from different organs, diseases, imaging devices, and other factors. While collecting data and labels from target domains is a feasible solution, annotating medical images is often tedious, expensive, and requires professionals. To address this problem, we combine active learning with domain-invariant feature learning. We propose a Domain-shift Active Learning (DistAL) framework, which includes a transferable feature learning algorithm and a hybrid sample selection strategy. Feature learning incorporates contrastive-consistency training to learn discriminative and domain-invariant features. The sample selection strategy is called RUDY, which jointly considers Representativeness, Uncertainty, and DiversitY. Its goal is to select samples from the unlabeled target domain for cost-effective annotation. It first selects representative samples to deal with domain shift, as well as uncertain ones to improve class separability, and then leverages K-means++ initialization to remove redundant candidates to achieve diversity. We evaluate our method for the task of lesion detection. By selecting only 1.7% samples from the target domain to annotate, DistAL achieves comparable performance to the method trained with all target labels. It outperforms other AL methods in five experiments on eight datasets collected from different hospitals, using different imaging protocols, annotation conventions, and etiologies.

PMID:40227902 | DOI:10.1109/TMI.2025.3558861

IEEE Trans Vis Comput Graph. 2025 Apr 14;PP. doi: 10.1109/TVCG.2025.3560345. Online ahead of print.

ABSTRACT

Matrix reordering permutes the rows and columns of a matrix to reveal meaningful visual patterns, such as blocks that represent clusters. A comprehensive collection of matrices, along with a scoring method for measuring the quality of visual patterns in these matrices, contributes to building a benchmark. This benchmark is essential for selecting or designing suitable reordering algorithms for revealing specific patterns. In this paper, we build a matrix-reordering benchmark, ReorderBench, with the goal of evaluating and improving matrix-reordering techniques. This is achieved by generating a large set of representative and diverse matrices and scoring these matrices with a convolution- and entropy-based method. Our benchmark contains 2,835,000 binary matrices and 5,670,000 continuous matrices, each generated to exhibit one of four visual patterns: block, off-diagonal block, star, or band, along with 450 real-world matrices featuring hybrid visual patterns. We demonstrate the usefulness of ReorderBench through three main applications in matrix reordering: 1) evaluating different reordering algorithms, 2) creating a unified scoring model to measure the visual patterns in any matrix, and 3) developing a deep learning model for matrix reordering.

PMID:40227900 | DOI:10.1109/TVCG.2025.3560345

J Vis Exp. 2025 Mar 28;(217). doi: 10.3791/67565.

ABSTRACT

Lung transplantation is a critical treatment for patients with end-stage lung diseases like idiopathic pulmonary fibrosis, but challenges such as donor shortages and posttransplant complications persist. Bioengineered lungs, integrating patient-specific cells into decellularized animal scaffolds, present a promising alternative. Despite progress in using bioengineered lungs in animal models, functionality and structure remain immature. This protocol addresses a critical barrier in organ bioengineering: the need for a cost-effective experimental platform. By using mouse models instead of larger animals like rats or swine, researchers can significantly reduce the resources required for each experiment, accelerating research progress. The protocol outlines a detailed procedure for lung bioengineering using mouse heart-lung blocks and human primary cells, focusing on isolation strategy for the mouse heart-lung block, decellularization, bioreactor setup, perfusion-based organ culture, and orthotopic transplantation of bioengineered lungs. This mouse-scale platform not only reduces experimental costs but also provides a viable framework for optimizing cell types and numbers for recellularization, testing different cell types using histological and molecular methods, and ensuring blood flow post-transplantation. The method holds potential for broad applications, including studying cell interactions in three-dimensional culture conditions, cell-matrix interactions, and ex vivo cancer modeling, thereby advancing the field of organ bioengineering.

PMID:40228017 | DOI:10.3791/67565

J Phys Chem B. 2025 Apr 14. doi: 10.1021/acs.jpcb.4c08792. Online ahead of print.

ABSTRACT

A classical problem in colloidal physics is the behavior of a spherical particle when it randomly walks close to the interface between a fluid and a rigid wall. Solutions to the two complementary aspects of this problem have been provided by Faxén and Brenner, respectively, based on continuum mechanics. Their results predict that the closer the particle is to the interface the slower it moves, but the pace of the slow-down depends on whether the particle steps parallel with or perpendicular to the interface; that is, the particle's diffusivity divaricates in a distance- and direction-dependent manner. While the theoretical predictions enjoy unequivocal experimental supports for μm-sized particles, their applicability on the smaller length scales remains unclear, however. Here we present the first direct experimental test for the complete Faxén-Brenner solutions on the nanoscale. Our experiment was enabled by a new multiresolution instrument which concurrently and synchronously recorded both the high-resolution lifetime-gated μs 3D tracking of a single diffusing nanoparticle for nanoscale diffusivity and the lower-resolution two-photon laser-scanning microscopy images for the nanoparticle's location relative to the wall interface. The directional diffusivity divarication predicted by Faxén and Brenner was reproduced on the single-nanoparticle level with no adjustable parameters. Our results thus provided experimental supports for the underlying fluid-dynamics physical picture down to ∼ 65 nm, the radius of the nanoparticle sample used in this work, and pointed to next experimental challenges being in the sub-100 nm regime where finite-temperature fluctuations and the molecularity of the fluid are expected to become increasingly noticeable for smaller nanoparticles.

PMID:40228157 | DOI:10.1021/acs.jpcb.4c08792

Biomacromolecules. 2025 Apr 14. doi: 10.1021/acs.biomac.4c01505. Online ahead of print.

ABSTRACT

Trehalose has sparked considerable interest in a variety of pharmaceutical applications as well as in cryopreservation. Recently, there have been growing efforts in the development of trehalose delivery nanocarriers to address the issue of the poor bioavailability of trehalose. The majority of the strategies comprise physical entrapment of trehalose, since its covalent, yet biolabile, conjugation is challenging. Here, we present research on trehalose-releasing nanogels, in which covalent, yet biolabile, conjugation of trehalose was achieved through the co-incorporation of trehalose (meth)acrylate(s) together with hydrophilic primary/secondary acrylamides in one polymeric network. In this case, the primary and secondary amide groups participated in ester hydrolysis in the (meth)acrylate units, making the hydrolysis feasible under physiologically relevant conditions. A set of nanogels with precisely selected compositions were synthesized, characterized, and then studied to evaluate the influence of various structural and environmental factors on the release rate of trehalose. The study also provides insights into some other aspects that are important in view of potential biomedical applications, including specific interactions of nanogels through their terminal α-d-glucopyranosyl moieties from pendant trehalose, protein corona formation, and cellular uptake.

PMID:40228144 | DOI:10.1021/acs.biomac.4c01505

Proc Natl Acad Sci U S A. 2025 Apr 22;122(16):e2504470122. doi: 10.1073/pnas.2504470122. Epub 2025 Apr 14.

NO ABSTRACT

PMID:40228138 | DOI:10.1073/pnas.2504470122

Proc Natl Acad Sci U S A. 2025 Apr 22;122(16):e2426385122. doi: 10.1073/pnas.2426385122. Epub 2025 Apr 14.

ABSTRACT

Insights into the molecular processes that drive early development of the human placenta is crucial for our understanding of pregnancy complications such as preeclampsia and fetal growth restriction, since defects in maturation of its epithelial cell, the trophoblast, have been detected in the severe forms of these diseases. However, key regulators specifying the differentiated trophoblast subtypes of the placenta are only slowly emerging. By using diverse trophoblast cell models, we herein show that the transcriptional coactivator of HIPPO signaling, TAZ, plays a pivotal role in the development of invasive extravillous trophoblasts (EVTs), cells that are essential for decidual vessel remodeling and adaption of maternal blood flow to the placenta. Ribonucleic acid sequencing (RNA-seq) or protein analyses upon TAZ gene silencing or CRISPR-Cas9-mediated knockout in differentiating trophoblast stem cells, organoids, primary EVTs, choriocarcinoma cells, or villous explant cultures unraveled that the coactivator promoted expression of genes associated with EVT identity, motility, and survival. Accordingly, depletion or chemical inhibition of TAZ, interacting with TEA domain family member 1 (TEAD1), impaired EVT differentiation, invasion, and migration and triggered apoptosis in the different trophoblast models. Notably, the coactivator also suppressed cell cycle genes and regulators of trophoblast self-renewal and prevented EVTs from cell fusion in organoids and primary cultures. Moreover, TAZ promoted human leukocyte antigen G (HLA-G) surface expression and increased NUAK1 kinase in EVTs thereby maintaining its own expression. In summary, the transcriptional coactivator TAZ plays a multifaceted role in the development of the EVT cell lineage by controlling different biological processes that initiate and preserve differentiation.

PMID:40228123 | DOI:10.1073/pnas.2426385122

Cancers (Basel). 2025 Mar 28;17(7):1144. doi: 10.3390/cancers17071144.

ABSTRACT

According to the European Federation of Pharmaceutical Industries and Association (EFPIA), a drug takes about 12-13 years from the first synthesis of a new active substance for the medicinal product to reach the market [...].

PMID:40227656 | DOI:10.3390/cancers17071144

Front Pharmacol. 2025 Mar 28;16:1564911. doi: 10.3389/fphar.2025.1564911. eCollection 2025.

ABSTRACT

Cancer is a leading cause of mortality worldwide, with most conventional treatments lacking efficacy and having significant challenges like drug resistance. Finding new molecules is quite challenging in terms of cost, time and setbacks. Hence, drug repurposing is considered sensible for skipping the long process of drug development. Dibenzazepine carboxamides, as traditional anticonvulsants, primarily function by blocking voltage-gated sodium channels, which not only mitigate seizures but also influence mood disorders through modulation of serotonin and dopamine. Recent studies have uncovered their anticancer properties, demonstrated by both in vitro and in vivo experiments. This review comprehensively examines dibenzazepine's pharmacodynamics, pharmacokinetics, and clinical applications, focusing on their emerging role in oncology. By highlighting the anticancer mechanisms of action-including apoptosis induction, inhibition of HDAC, Wnt/β-Catenin signaling, and Voltage-gated sodium channels, we suggest further research to fully elucidate their therapeutic potential and application in cancer treatment.

PMID:40223925 | PMC:PMC11985771 | DOI:10.3389/fphar.2025.1564911

Hum Mutat. 2025 Feb 27;2025:6096758. doi: 10.1155/humu/6096758. eCollection 2025.

ABSTRACT

Affecting fewer than 20,000 people as defined in South Korea, rare diseases pose significant diagnostic challenges due to their diverse manifestations and genetic heterogeneity. Genome sequencing (GS) offers a promising solution by enabling simultaneous screening for thousands of rare genetic disorders. This study explores the diagnostic utility and necessity of GS within the government-funded Korean Regional Rare Disease Diagnostic Support Program (KR-RDSP), a collaborative initiative involving 11 regional rare disease centers across Korea. The program was launched as a proof-of-concept study in 2023 to equip the genetic clinics with a diagnostic tool to expedite the diagnoses for rare disease patients who reside outside the urban Seoul region where diagnostic resources are limited. The study leveraged GS to diagnose a cohort of 400 patients exhibiting a wide spectrum of symptoms. The overall diagnostic yield was 36.3% (145/400), with 4.8% (7/145) of the diagnosed patients being reported with variants that could not have been identified by chromosomal microarray or exome sequencing (ES), highlighting the added value of comprehensive genomic analysis. The implementation of a centralized GS analysis system streamlined the diagnostic process, enabling timely reporting within a reasonable turnaround time of ≤ 35 days. Segregation analysis by Sanger sequencing played a crucial role in confirming or reclassifying variant pathogenicity by elucidating inheritance patterns. Here, we summarize diagnostic statistics from the 400 GS dataset gathered from June 2023 to December 2023 and show interesting and informative case examples that illustrate the diagnostic efficacy of GS, highlighting its ability to uncover elusive genetic etiologies and provide personalized treatment insights. The study also highlights the successful implementation of the program for the 11 regional rare disease centers across Korea with a practical workflow, comprehensive testing, comparable diagnostic yield to previous reports, and, most importantly, reasonable turnaround time.

PMID:40226308 | PMC:PMC11987077 | DOI:10.1155/humu/6096758

Hum Mutat. 2024 Apr 29;2024:6411444. doi: 10.1155/2024/6411444. eCollection 2024.

ABSTRACT

Clinical exome and genome sequencing (ES/GS) have become indispensable diagnostic tools for rare genetic diseases (RGD). However, the interpretation of ES/GS presents a substantial operational challenge in clinical settings. Test interpretation requires the review of hundreds of genetic variants, a task that has become increasingly challenging given the rising use of ES/GS. In response, we present Clinical Assessment of Variants by Likelihood Ratios (CAVaLRi), which employ a modified likelihood ratio (LR) framework to assign diagnostic probabilities to candidate germline disease genes. CAVaLRi models aspects of the clinical variant assessment process, taking into consideration the predicted impact of the variant, the proband and parental genotypes, and the proband's clinical characteristics. It also factors in computational phenotype noise and weighs the relative significance of genotype, phenotype, and variant segregation information. We trained and tested CAVaLRi on variant and phenotype data from an internal cohort of 655 clinical ES cases. For validation, CAVaLRi's performance was benchmarked against four leading gene prioritization algorithms (Exomiser's hiPHIVE and PhenIX prioritizers, LIRICAL, and XRare) using a distinct cohort of 12,832 ES cases. Our findings reveal that CAVaLRi significantly outperforms its counterparts when clinician-curated phenotype sets are used, as evidenced by its superior precision-recall curve (PR AUC: 0.701) and average diagnostic gene rank (1.59). Notably, even when substituting highly focused clinician-curated phenotype sets with large and potentially nonspecific computationally derived phenotypes, CAVaLRi retains its precision (PR AUC: 0.658; diagnostic gene average rank: 1.68) and markedly outperforms other tools. In a large, heterogeneous validation cohort, CAVaLRi stood out as the most precise prioritization algorithm (PR AUC: 0.335; average diagnostic rank: 1.91). In conclusion, CAVaLRi presents a robust solution for prioritizing diagnostic genes, surpassing current methods. It demonstrates resilience to noisy, computationally-derived phenotypes, providing a scalable strategy to help labs focus on the most diagnostically relevant variants, thus addressing the growing demand for ES/GS interpretation.

PMID:40225936 | PMC:PMC11918498 | DOI:10.1155/2024/6411444

Hum Mutat. 2024 Apr 18;2024:9920230. doi: 10.1155/2024/9920230. eCollection 2024.

ABSTRACT

Although around 6% of the world's population is affected by rare diseases, only a small number of disease-modifying therapies are available. In recent years, antisense oligonucleotides (ASOs) have emerged as one option for the development of therapeutics for orphan diseases. In particular, ASOs can be utilized for individualized genetic treatments, addressing patients with a known disease-causing genetic variant, who would otherwise not be able to receive therapy. Careful prioritization of genetic variants amenable to an ASO approach is crucial to increase chances for successful treatments and reduce costs and time for drug development. At present, there is no consensus on how to systematically approach this selection procedure. Here, we present practical guidelines to evaluate disease-causing variants and standardize the process of selecting n-of-1 cases. We focus on variants leading to a loss of function in monogenic disorders and consider which splice-switching ASO-mediated treatments are applicable in each case. To ease the understanding and application of our guidelines, we created a hypothetical transcript covering different pathogenic variants and explained their evaluation in detail. We support our recommendations with real-life examples and add further considerations to be applied to specific cases to provide a comprehensive framework for selecting eligible variants.

PMID:40225926 | PMC:PMC11919232 | DOI:10.1155/2024/9920230

Depress Anxiety. 2024 Mar 25;2024:2057881. doi: 10.1155/2024/2057881. eCollection 2024.

ABSTRACT

AIM: To determine serum concentrations of leptin and ghrelin in patients with major depressive disorder (MDD) before and after vitamin D3 supplementation.

METHODS: A total of 72 participants were recruited in this study (40 MDD patients and 32 healthy controls). MDD was diagnosed by using Beck's Depression Inventory (BDI) scale. Blood samples were collected from all participants at the beginning of the study to determine baseline serum 25(OH)D3, leptin, and ghrelin concentrations. Patients were then treated weekly with vitamin D3 (50,000 IU) for 3 months, and blood samples were collected again by the end of the study.

RESULTS: At baseline, serum leptin concentrations were significantly higher in MDD patients than in healthy controls. In contrast, serum ghrelin concentrations were significantly lower compared to those in healthy controls. After supplementation with vitamin D3 for three months, MDD patients showed improvements characterized by a decrease in their BDI's scores and an increase in their serum vitamin D and ghrelin concentrations. No effects of vitamin D3 supplementation were seen on serum leptin concentration.

CONCLUSIONS: The antidepressant effects of vitamin D3 supplementation could be mediated by ghrelin but not leptin.

PMID:40226697 | PMC:PMC11918899 | DOI:10.1155/2024/2057881

Front Pharmacol. 2025 Mar 28;16:1523536. doi: 10.3389/fphar.2025.1523536. eCollection 2025.

ABSTRACT

INTRODUCTION: Since April 2020, pretherapeutic screening for accessing the deficiency of the DPD enzyme by genotyping the dihydropyrimidine dehydrogenase gene (DPYD) is required by the European Medicine Agency (EMA) prior to the administration of fluoropyrimidine-based chemotherapy. In May 2020, the Spanish Drug and Medical Devices Agency (AEMPS) published an informative note highlighting the importance of DPYD analysis prior fluoropyrimidines derivatives administration to prevent the development of severe adverse drug reactions (ADRs). The publication of these recommendations marked a turning point in the daily routine in many pharmacogenetics laboratories in Spain. This article aims to illustrate the current state of the DPYD testing in the reference genomic medicine center in Galicia, 4 years after the EMA's updated recommendations.

METHODS: The Pharmacogenetics Unit in the reference genomic medicine center conducted genotyping of the four DPYD variants recommended by regulatory agencies that oncologists can adjust fluoropyrimidine treatment based on DPYD genotype results.

RESULTS: Between 1 June 2020 to 1 May 2024, both included, a total of 2,798 DPYD requests were analyzed. DPYD genotyping results revealed a 3.15% prevalence of heterozygosity for at least one of the four DPYD variants, being rs56038477 the most prevalent variant (1.31%).

CONCLUSION: This study addresses the importance of the DPYD analysis implementation in clinical practice after the changes in EMA and AEMPs recommendations which has led to a significant increase in DPYD genotyping requests. This highlights the significance of preemptive genotyping for accurately adjusting fluoropyrimidines doses before initiating treatment.

PMID:40223928 | PMC:PMC11985815 | DOI:10.3389/fphar.2025.1523536

Acta Inform Med. 2025;33(1):54-57. doi: 10.5455/aim.2024.33.54-57.

ABSTRACT

BACKGROUND: Out of 25-30% of individuals do not respond to 5-Alpha Reductase Inhibitors (5-ARI) as a primary treatment of Benign Prostatic Hyperplasia (BPH), 7% experience disease progression despite treatment. Personalized medicine, which leverages human genomics, offers an approach to tailor treatments based on individual genetic profiles, facilitating early detection of drug resistance and optimizing therapeutic strategies.

OBJECTIVE: The aim of the study was to advance personalized medicine in BPH by identifying genetic factors that influence treatment outcomes, thus improving therapeutic efficacy.

METHODS: This cohort study involved patients responsive and resistant to treatment of BPH. After prostate resection, DNA was extracted and subjected to protein sequencing. The quality of the DNA was assessed, and next-generation sequencing (NGS) was performed. The sequencing data analyzed using FastQC, Samtools, MuTect2, ANNOVAR, and VEP. Whole-genome sequencing (WGS) data were compared to the Human GRCh38 reference genome. Single nucleotide polymorphisms (SNPs) and their positions were visualized through Integrated Genomics Viewer (IGV). Statistical analyses were conducted using R software.

RESULT: Two genetic variants associated with BPH, was a single nucleotide polymorphism (SNP) in the NOS3 gene at rs1799983 (T>A/G), and an SNP at rs61767072 in the SRD5A2 gene. All samples that exhibited resistance to combination drug therapy showed mutations in SNP rs61767072, specifically a deletion at base A in the SRD5A2 gene. Strong correlation reported between SNP rs61767072 and resistance to BPH combination therapy while mutations involving base A and base G in the NOS3 gene did not exhibit any significant correlation with resistance to BPH combination therapy.

CONCLUSION: Variations in genetic makeup significantly affect personalized medical care. Identification of specific SNPs such as rs61767072 may be the basis for the development of more personalized therapies. This study provides evidence that pharmacogenomic approaches are needed in urology practice to improve treatment outcomes.

PMID:40223852 | PMC:PMC11986343 | DOI:10.5455/aim.2024.33.54-57

Antioxidants (Basel). 2025 Mar 4;14(3):310. doi: 10.3390/antiox14030310.

ABSTRACT

A critical challenge in the age of advanced modulator therapies is to understand and determine how effectively chronic oxidative stress and oxidative stress-induced inflammation can be reversed and physiological balance restored when CFTR function is pharmacologically improved. The triple therapy with elexacaftor-tezacaftor-ivacaftor (ETI) suggests that CFTR activity in individuals with at least one F508del mutation can be partially restored to about 50% of normal levels. Although incomplete, the partial recovery of CFTR function has been shown to drastically lower sputum pathogen content, enhance microbiome diversity, and lower inflammation markers within the first year of treatment in adolescents and adults with cystic fibrosis. However, despite these advancements, residual airway infection, oxidative stress and inflammation persist, with levels similar to other chronic lung conditions, like non-CF bronchiectasis. This persistence highlights the necessity for innovative antioxidant and anti-inflammatory treatments, in particular for individuals with advanced lung disease. To address this issue, emerging multi-omics technologies offer valuable tools to investigate the impact of modulator therapies on various molecular pathways. By analyzing changes in gene expression, epigenetic modifications, protein profiles and metabolic processes in airway-derived samples, it could be possible to uncover the mechanisms driving persistent oxidative stress and inflammation. These insights could pave the way for identifying new therapeutic targets to fully restore airway health and overall physiological balance.

PMID:40227282 | DOI:10.3390/antiox14030310

Pediatr Pulmonol. 2025 Apr;60(4):e71084. doi: 10.1002/ppul.71084.

ABSTRACT

OBJECTIVE: The primary objective of this study was to examine the performance of the Asthma Clinical Score (ACS) relative to the Pediatric Respiratory Assessment Measure (PRAM). Our secondary objectives were to determine interrater reliability, discriminative validity, responsiveness, and predictive validity of the ACS and PRAM.

METHODS: This was a single-site prospective observational study of children ages 2 to < 18 years presenting to the emergency department (ED) for asthma exacerbations. Clinicians completed paired assessments using ACS and PRAM at three time points of each patients ED stay. Construct validity correlating the performance of the ACS to PRAM, and interrater reliability were analyzed using Spearmen's rank correlation coefficients and Cohen's kappa coefficient, respectively. Cohen's d was calculated to compare the scores of patients who received certain treatments to patients who did not. Reliable change index (RCI) was used to determine the responsiveness of each score. Predictive validity for hospitalization was analyzed using Area Under the Receiver Operating Characteristic curve (AUROCc) and Akaike Information Criterion (AIC).

RESULTS: 399 children were enrolled with 338 paired clinician observations. The ACS and PRAM scores were strongly correlated at all time points (n = 1383, ρ $\rho $ = 0.874). Both the ACS and PRAM showed moderate interrater reliability at all time points (n = 338, κw = 0.77 and κw = 0.69, respectively). Patients receiving albuterol nebulization or adjunctive medications had higher average ACS and PRAM scores. ACS showed a better ability to detect responsiveness than the PRAM (31% vs 15% respectively). The pretreatment ACS showed comparable predictive validity to the PRAM.

CONCLUSION: The ACS was highly correlated with PRAM and is a reliable score in this cohort. The ACS showed good discriminative validity, predictive validity and responsiveness. This study supports the ACS as a useful tool in ED assessment of asthma exacerbation severity in children.

PMID:40226890 | DOI:10.1002/ppul.71084

Cell Biomater. 2025 Mar 25;1(2):100013. doi: 10.1016/j.celbio.2025.100013. Epub 2025 Mar 3.

ABSTRACT

Mucociliary clearance (MCC) is critical in maintaining lung health and preventing respiratory infections. MCC is impaired in people with cystic fibrosis, due to accumulation of thick, sticky mucus resulting from defective cystic fibrosis transmembrane conductance regulator channel function. In this study, we developed a unique 3D lung submucosal gland ductal airway model utilizing primary human submucosal gland epithelial cells, which enables the formation of physiologically relevant architecture of the ductal epithelium including ciliary cells within a 3D bioprinted scaffold. Our observation demonstrates that this model not only enables the fabrication of human lung submucosal gland ductal airway-like structure mimicking in vivo physiology, also facilitates quantitative measurement of patient-specific MCC and determines pharmacological effects. Our results suggest that this model could be a valuable tool for understanding mechanisms underlying impaired MCC and testing the efficacy of novel therapeutic strategies for the treatment of respiratory diseases such as cystic fibrosis.

PMID:40226365 | PMC:PMC11984632 | DOI:10.1016/j.celbio.2025.100013