J Infect Public Health. 2025 Mar 19;18(6):102763. doi: 10.1016/j.jiph.2025.102763. Online ahead of print.

ABSTRACT

BACKGROUND: Leprosy and tuberculosis caused by Mycobacterium leprae and Mycobacterium tuberculosis, respectively, are chronic infections with significant public health implications. While leprosy affects the skin and peripheral nerves and tuberculosis primarily targets the lungs, both diseases involve systemic immune responses. This study integrates transcriptomic analysis cheminformatics and molecular dynamics simulations to identify molecular mechanisms and potential therapeutic targets.

METHODS: Transcriptomic datasets were analyzed to identify dysregulated genes and pathways. Pathway enrichment tissue-specific and bulk RNA-seq expression analyses provided biological context. System biology networks revealed regulatory hub genes and molecular docking studies evaluated CHEMBL compounds as potential therapeutics. Molecular dynamics (MD) simulations assessed the stability of top ligand-protein complexes through RMSD RMSF and MM-GBSA free energy calculations.

RESULTS: Gene expression analysis identified 13 core dysregulated genes, including HSP90AA1 MAPK8IP3 and ZMPSTE24. Tissue-specific expression localized pivotal genes to lung tissues and immune cells with HSP90AA1 highly expressed in alveolar macrophages and epithelial cells. HSP90AA1 gene emerged as a central hub gene with 96 interactions involved in stress response pathways. Docking studies identified CHEMBL3653862 and CHEMBL3653884 with strong binding affinities (-10.16 to -12.69 kcal/mol) interacting with Asp93 and Tyr139. MD simulations confirmed binding stability with RMSD fluctuations within 2.1-3.5 Å and MM-GBSA energy values supporting ligand-protein stability.

CONCLUSION: This study identifies HSP90AA1 as a potential drug target in leprosy and tuberculosis. Findings support host-directed therapy approaches and highlight the importance of computational modeling in accelerating drug discovery. The study provides a foundation for future experimental validation, including in vitro and in vivo testing to advance drug repurposing strategies for these chronic infections.

PMID:40153981 | DOI:10.1016/j.jiph.2025.102763

Bull Cancer. 2025 Mar;112(3S1):3S107-3S116. doi: 10.1016/S0007-4551(25)00164-X.

ABSTRACT

In Europe, a rare cancer is defined as having an incidence rate of less than 6/100,000. Rare lung cancers encompass many entities defined by the 2021 WHO classification of thoracic tumors, and represent around 10% of all lung cancers. Rare lung cancers involve several histological types (carcinoma, sarcoma and lymphoma), each of which comprises several entities. The management of these patients with rare cancers requires specific medical expertise at every level (diagnosis, treatment and follow-up). These patients should therefore be referred to expert centers affiliated with national networks, giving them appropriate care and better access to innovative treatments. The deployment of systematic molecular characterization of these tumors has allowed for the identification and better characterization of specific entities. Some entities are specific to the lung, while others are more commonly found in other organs. In this review, we will only consider malignant lung tumors with an incidence of less than 1%.

PMID:40155070 | DOI:10.1016/S0007-4551(25)00164-X

J Pharm Sci. 2025 Mar 26:103772. doi: 10.1016/j.xphs.2025.103772. Online ahead of print.

ABSTRACT

OATP2B1, encoded by SLCO2B1, is a drug transporter expressed widely throughout the body in tissues such as the intestine and liver. Genetic variation of this transporter may lead to altered disposition of OATP2B1 substrate drugs, but especially the effects of rare variants are poorly understood. The aim of this study was to characterize the effects of naturally occurring missense single nucleotide variants of SLCO2B1 (c.601G>A, c.935G>A, c.953C>T, c.1175C>, c.1457C>T, c.1559G>C, c.1596C>A, and the c.601G>A + c.935G>A haplotype) on the in vitro functionality of OATP2B1. To characterize transport activity, cellular uptake of dibromofluorescein, 5-carboxyfluorescein, estrone sulfate, and rosuvastatin was compared in OATP2B1 reference- and variant-expressing HEK293 cells. The abundance of OATP2B1 variants in HEK293 crude membrane preparations was quantified with LC-MS/MS-based quantitative targeted absolute proteomics analysis. Variant c.1559G>C impaired OATP2B1-mediated uptake of all tested substrates almost completely, but protein abundance was not reduced to the same extent. Other studied variants had comparable or only modestly reduced protein abundance and transport function compared to reference OATP2B1. These results can be utilized to understand findings from clinical pharmacogenetic studies. More importantly, the results can aid in predicting the consequences of rare variants, such as the loss-of-function variant c.1559G>C, which can be difficult to detect in clinical studies.

PMID:40154787 | DOI:10.1016/j.xphs.2025.103772

Semin Cancer Biol. 2025 Mar 26:S1044-579X(25)00051-3. doi: 10.1016/j.semcancer.2025.03.002. Online ahead of print.

ABSTRACT

Pancreatic cancers have high mortality and rising incidence rates which may be related to unhealthy western-type dietary and lifestyle patterns as well as increasing body weights and obesity rates. Recent data also suggest a role for the gut microbiome in the development of pancreatic cancer. Here, we review the experimental and observational evidence for the roles of the oral, gut and intratumoural microbiomes, impaired gut barrier function and exposure to inflammatory compounds as well as metabolic dysfunction as contributors to pancreatic disease with a focus on pancreatic ductal adenocarcinoma initiation and progression. We also highlight some emerging gut microbiome editing techniques currently being investigated in the context of pancreatic disease. Notably, while the gut microbiome is significantly altered in PDAC and its precursor diseases, its utility as a diagnostic and prognostic tool is hindered by a lack of reproducibility and the potential for reverse causality in case-control cohorts. Future research should emphasise longitudinal and mechanistic studies as well as integrating lifestyle exposure and multi-omics data to unravel complex host-microbiome interactions. This will allow for deeper aetiologic and mechanistic insights that can inform treatments and guide public health recommendations.

PMID:40154652 | DOI:10.1016/j.semcancer.2025.03.002

J Biol Chem. 2025 Mar 26:108460. doi: 10.1016/j.jbc.2025.108460. Online ahead of print.

ABSTRACT

Activation of the cystic fibrosis transmembrane conductance regulator (CFTR) Cl‒ channel requires PKA phosphorylation at the regulatory (R) domain to relieve inhibition of ATP-dependent channel activity. This study aimed to identify the primary inhibitory site that prevents channel activation. CFTR mutants with deletion of residues 760-783 (ΔR760-783) elicited constitutive macroscopic and single-channel Cl‒ currents in the presence of ATP before PKA phosphorylation, suggesting that protein segment R760-783 in the R domain blocks CFTR activation. With the background of ΔR760-835, further deletion of R708-759 led to fully active channels in the presence of ATP, but absence of PKA, suggesting that R708-759 prevents the activation of ΔR760-835-CFTR. R760-783 peptides were unstructured in buffered solutions in circular dichroism spectroscopy and the N771P mutation that interrupts the α-helix formation induced no apparent constitutive current before PKA phosphorylation. These data suggest that interpeptide interactions by α-helices likely contribute trivially to the blocking effect of R760-783. CFTR mutants with small deletions or alanine replacements containing any one of residues R766 and S768 in a PKA consensus sequence and M773 and T774 generated PKA-independent CFTR Cl‒ currents. Similarly, introducing the mutations Q767C or T774C into a control CFTR construct produced constitutive CFTR Cl‒ currents by positively charged MTSET modification of target cysteines. Moreover, PKA-independent single-channel activity was evidently observed in R766K-, S768K- and T774K-CFTR mutants. Therefore, the four residues R766, S768, M773 and T774 may form an inhibitory module that precludes CFTR activation through side-chain interactions. This inhibitory mechanism might be emulated by other PKA-dependent proteins.

PMID:40154618 | DOI:10.1016/j.jbc.2025.108460

Eur Respir J. 2025 Mar 28:2402249. doi: 10.1183/13993003.02249-2024. Online ahead of print.

ABSTRACT

BACKGROUND: Patients with severe COVID-19 may develop lung fibrosis. Pirfenidone is an anti-fibrotic drug approved for idiopathic pulmonary fibrosis. The efficacy and safety of pirfenidone in patients with fibrotic interstitial lung changes after recovery from severe COVID-19 pneumonia was evaluated.

METHODS: Phase 2, double-blind, placebo-controlled, Spanish multicenter clinical trial randomized to receive pirfenidone or placebo (2:1) for 24-weeks. The primary endpoint was the proportion of patients that improved, considered when percent change in forced vital capacity (FVC) was ≥10% and/or any reduction in the fibrotic score chest high-resolution computed tomography (HRCT). Secondary endpoints included health-related quality of life (HRQoL), exercise capacity, and drug safety profile.

RESULTS: From 119 eligible patients, 113 were randomized and 103 were analyzed (pirfenidone n=69, placebo n=34). Most patients were male (73.5%) and were receiving low-dose prednisone; mean age was 63.7 years and body-mass index was 29 kg·m-2. The percentage of patients that improved was similar in the pirfenidone and placebo groups (79.7% versus 82.3%, respectively). The mean predicted FVC (%) increased 12.74 (20.6) with pirfenidone and 4.35 (22.3) with placebo (p=0.071), and the HRCT (%) fibrotic score reduced 5.44 (3.69) with pirfenidone and 2.57 (2.59) with placebo (p=0.52). Clinically meaningful improvement in HRQoL was not statistically different (55.2% in pirfenidone and 39.4% in placebo group, respectively). Exercise capacity, adverse events and hospitalizations were similar between groups. No deaths were reported.

CONCLUSIONS: The overall improvement in lung function and the HRCT fibrotic score after 6 months with pirfenidone was not significantly different than placebo.

PMID:40154560 | DOI:10.1183/13993003.02249-2024

Cancer Cell. 2025 Mar 20:S1535-6108(25)00108-4. doi: 10.1016/j.ccell.2025.03.007. Online ahead of print.

ABSTRACT

Myeloid cancers such as myelodysplastic syndromes (MDS) and acute myeloid leukemia (AML) remain resistant to standard of care (SOC) and targeted therapies. In this study, we demonstrate that responsiveness to therapy is associated with activation of β-catenin-JAG1 in osteoblastic cells of patients treated with all-trans-retinoic acid (ATRA). ATRA suppresses β-catenin activity in patients and leukemic mice. Consequently, it inhibits the growth and survival of MDS/AML cells from patients with active β-catenin-JAG1 signaling and promotes their differentiation. This occurs independently of cytogenetics and mutational profile. ATRA also improves disease outcome in mice with no evidence of relapse and a superior safety profile to SOC. A human anti-JAG1 antibody improves efficacy in leukemic mice and patient-derived MDS/AML cells. β-catenin activation provides an explanation for the differential response to ATRA and a mechanistic biomarker for ATRA repurposing in myeloid malignancies, potentially evading relapse and extending across a broad range of cancers.

PMID:40154481 | DOI:10.1016/j.ccell.2025.03.007

J Immunother Cancer. 2025 Mar 28;13(3):e011273. doi: 10.1136/jitc-2024-011273.

ABSTRACT

INTRODUCTION: Immune checkpoint inhibitors (ICIs) can yield remarkable clinical responses in subsets of patients with solid tumors, but they also commonly cause immune-related adverse events (irAEs). The predictive features of clinically severe irAEs leading to cessation of ICIs have yet to be established. Given the similarities between irAEs and autoimmune diseases, we sought to investigate the association of a germline polygenic risk score for autoimmune disease and discontinuation of ICIs due to irAEs.

METHODS: The Genetics of immune-related adverse events and Response to Immunotherapy (GeRI) cohort comprises 1302 patients with non-small cell lung cancer (NSCLC) who received ICI therapy between 2009 and 2022 at four academic medical centers. We used a published polygenic risk score for autoimmune diseases (PRSAD) in the general population and validated it in the All of Us. We then assessed the association between PRSAD and cessation of ICI therapy due to irAEs in the GeRI cohort, using cause-specific and Fine-Gray subdistribution hazard models. To further understand the differential effects of type of therapy on the association between PRSAD and cessation of ICI due to irAEs, we conducted a stratified analysis by type of ICI therapy.

RESULTS: Using a competing risk model, we found an association between PRSAD and ICI cessation due to irAEs (HR per SD=1.24, p=0.004). This association was particularly strong in patients who had ICI cessation due to irAEs within 3 months of therapy initiation (HR per SD=1.40, p=0.005). Individuals in the top quintile of PRSAD had 4.8% ICI discontinuation for irAEs by 3 months, compared with 2% discontinuation by 3 months among patients in the bottom quintile (log-rank p=0.03). In addition, among patients who received combination programmed cell death protein-1 (PD-1)/programmed death-ligand 1 (PD-L1) inhibitors and cytotoxic T-lymphocyte associated protein 4 (CTLA4) inhibitors, ICI discontinuation for irAEs by 3 months occurred in 4 of the 13 patients (30.8%) with high PRSAD genetic risk (top quintile) versus 3 of 21 patients (14.3%) with low PRSAD genetic risk (bottom quintile).

CONCLUSIONS: We demonstrate an association between a polygenic risk score for autoimmune disease and early ICI discontinuation for irAEs. Our results suggest that germline genetics may be used as an adjunctive tool for risk stratification around ICI clinical decision-making in solid tumor oncology.

PMID:40154961 | DOI:10.1136/jitc-2024-011273

PLoS One. 2025 Mar 28;20(3):e0304540. doi: 10.1371/journal.pone.0304540. eCollection 2025.

ABSTRACT

The primary objective is to identify which observational research methods have been used in the last 5 years in rare disease drug evaluation and how they are applied to generate adequate evidence regarding the real-world effectiveness or safety of rare disease drugs. Rare disease is an umbrella term for a condition which affects < 200,000 people each year and despite the rarity of these conditions, collectively they encompass approximately 7000 different conditions. With the striking number of rare conditions, many pharmaceutical manufacturers are introducing an increased number of drugs to treat them. However, due to small patient populations, heterogeneity and other factors related to rare diseases, there are feasibility concerns regarding the generation of adequate efficacy and safety evidence using conventional randomized controlled trials (RCTs). Recently, real-world evidence generated through observational (or real-world) studies has been proposed to address some of the feasibility concerns with RCTs by measuring drug effectiveness or safety in the real-world setting. However, there remain methodological concerns due to a lack of randomization/masking. This proposed scoping review aims to identify which observational research methods in the last 5 years are used in rare disease drug evaluation to address methodological concerns and how they are applied to generate evidence on drug effectiveness or safety. Articles must be primary observational or real-world studies reporting rare disease drug effectiveness or safety published within the five years preceding this review. Literature reviews, meta-analyses, randomized control trials, case series, case reports, opinion pieces, conference abstracts, and studies with unavailable full-text articles will be excluded. The search strategy will combine the following key search concepts: rare disease, drugs for rare disease and observational/real-world studies. The search will be conducted in MEDLINE and EMBASE. Review registration number: Open Science Framework, https://osf.io/f3wpv.

PMID:40153394 | DOI:10.1371/journal.pone.0304540

Am J Respir Crit Care Med. 2025 Mar 28. doi: 10.1164/rccm.202409-1792OC. Online ahead of print.

ABSTRACT

RATIONALE: Mycobacteroides abscessus infections affect immunocompromised patients and those with underlying pulmonary disease. Conventional imaging cannot distinguish M. abscessus infections from underlying pulmonary disease or sterile inflammation, requiring invasive procedures for definitive diagnosis.

OBJECTIVE: We evaluated 11C-para-aminobenzoic acid (11C-PABA), a chemically identical radioanalog of PABA, to detect and localize infections due to M. abscessus.

METHODS: In vitro uptake assays were performed to test the metabolism and accumulation of PABA into M. abscessus reference and clinical isolates. Dynamic 11C-PABA positron emission tomography (PET) was performed in a mouse model of M. abscessus pulmonary infection and in a patient with microbiologically-confirmed M. abscessus pulmonary infection (NCT05611905).

MAIN RESULTS: 11C-PABA was intracellularly metabolized by M. abscessus to 11C-7,8-dihydropteroate. Additionally, and the reference and all thirteen randomly chosen clinical isolates, including three resistant to trimethoprim-sulfamethoxazole, rapidly accumulated PABA. No PABA accumulation was noted by heat-inactivated bacteria or mammalian cells. Dynamic 11C-PABA PET in a mouse model of M. abscessus pulmonary infection rapidly distinguished infection from sterile inflammation and also accurately monitored response to antibiotic treatment. Finally, dynamic 11C-PABA PET in a 33-year-old female with cystic fibrosis and microbiologically confirmed M. abscessus pulmonary infection was safe and demonstrated significantly higher and sustained PET uptake in the affected lesions.

CONCLUSIONS: 11C-PABA PET is an innovative, clinically-translatable, noninvasive, bacteria-specific diagnostic to differentiate M. abscessus infections from underlying pulmonary disease in patients. This tool could also help in monitoring treatment responses and enable precision medicine approaches for patients with complicated infections. This article is open access and distributed under the terms of the Creative Commons Attribution Non-Commercial No Derivatives License 4.0 (http://creativecommons.org/licenses/by-nc-nd/4.0/).

PMID:40153540 | DOI:10.1164/rccm.202409-1792OC

J Proteome Res. 2025 Mar 28. doi: 10.1021/acs.jproteome.4c00827. Online ahead of print.

ABSTRACT

Intercellular communication is important for host immunity in response to bacterial infections. Nontuberculous mycobacterium (NTM), such as Mycobacterium abscessus (M. ab), is a group of environmental bacteria that can cause severe lung infections in individuals with pre-existing lung conditions, including cystic fibrosis (CF) and chronic obstructive pulmonary disease (COPD). There is limited knowledge understanding the interaction between airway epithelial cells and immune cells during NTM infections. In this study, we characterized microvesicles (MVs) released from uninfected and M. ab-infected human bronchial epithelial cells and investigated the effect of these MVs on the activation and polarization of THP-1-derived macrophages in cell culture. Our results indicate that MVs released by M. ab-infected human bronchial epithelial cells stimulated the activation of M2-polarized macrophages in cell culture when compared to MVs released by uninfected cells. Additionally, the proteomic analysis for isolated MVs showed that the proteins involved in the cell adhesion pathway were enriched in MVs from M. ab-infected human bronchial epithelial cells compared to MVs from uninfected cells. Among those, the cell surface protein, intercellular adhesion molecule 1 (ICAM-1), regulated the uptake of MVs released by M. ab-infected human bronchial epithelial cells by recipient macrophages in cell culture. In conclusion, our data suggest that in response to M. ab infection, human airway epithelial cells release MVs to modulate the activation of macrophages, which are key cells for mycobacterial intracellular survival in the host.

PMID:40153482 | DOI:10.1021/acs.jproteome.4c00827

Lung. 2025 Mar 28;203(1):55. doi: 10.1007/s00408-025-00806-6.

ABSTRACT

PURPOSE: Cystic fibrosis (CF) is a genetic disease caused by mutations in the CFTR gene, leading to multisystemic complications, particularly in the lungs. CFTR dysfunction results in altered ion transport, chronic inflammation, and progressive lung damage. The triple therapy elexacaftor/tezacaftor/ivacaftor (ETI) has demonstrated significant improvements in pulmonary function and quality of life. This study aimed to evaluate the anti-inflammatory effects of ETI by analysing systemic cytokine profiles over 12 months.

METHODS: A prospective study included 32 CF patients ≥ 18 years with at least one delF508 mutation, undergoing ETI therapy. Clinical stability was ensured prior to therapy initiation. Demographic data, BMI (Body Mass Index), FEV1% (Forced expiratory Volume in the first second), VR/TLC (residual volume/total lung capacity) and sweat chloride concentrations were recorded at baseline, 6 months and 12 months. Inflammatory markers, including fibrinogen, C-reactive protein (CRP), and a panel of 8 cytokines, were measured using multiplex bead-based immunoassays and electrochemiluminescence. Longitudinal changes were analysed using mixed-effects models and statistical tests, with significance set at p < 0.05.

RESULTS: During a 12-month follow-up, the neutrophils number and proinflammatory biomarkers analyzed, fibrinogen, CRP, GM-CSF, IFN- γ, IL-1 α, IL-1 β, IL-8 (CXCL8), IL-12p70, IL-17A (CTLA-8), and TNF-α, significantly decreased, while eosinophils remained stable. Mixed-effects models confirmed the significant association of inflammatory biomarkers with FEV1, BMI, sweat chloride levels, and VR/TLC highlighting the role of inflammation in the progression of CF.

CONCLUSIONS: ETI demonstrated marked anti-inflammatory effects in CF patients, reducing systemic inflammation and improving clinical parameters.

PMID:40153049 | DOI:10.1007/s00408-025-00806-6

PLoS One. 2025 Mar 28;20(3):e0321409. doi: 10.1371/journal.pone.0321409. eCollection 2025.

ABSTRACT

[This corrects the article DOI: 10.1371/journal.pone.0312112.].

PMID:40153338 | DOI:10.1371/journal.pone.0321409

IEEE Trans Pattern Anal Mach Intell. 2025 Mar 28;PP. doi: 10.1109/TPAMI.2025.3556133. Online ahead of print.

ABSTRACT

Recent years have witnessed significant advances in image deraining due to the progress of effective image priors and deep learning models. As each deraining approach has individual settings (e.g., training and test datasets, evaluation criteria), how to fairly evaluate existing approaches comprehensively is not a trivial task. Although existing surveys aim to thoroughly review image deraining approaches, few of them focus on unifying evaluation settings to examine the deraining capability and practicality evaluation. In this paper, we provide a comprehensive review of existing image deraining methods and provide a unified evaluation setting to evaluate their performance. Furthermore, we construct a new high-quality benchmark named HQ-RAIN to conduct extensive evaluations, consisting of 5,000 paired high-resolution synthetic images with high harmony and realism. We also discuss existing challenges and highlight several future research opportunities worth exploring. To facilitate the reproduction and tracking of the latest deraining technologies for general users, we build an online platform to provide the off-the-shelf toolkit, involving the large-scale performance evaluation. This online platform and the proposed new benchmark are publicly available at http://www.deraining.tech/.

PMID:40153286 | DOI:10.1109/TPAMI.2025.3556133

IEEE J Biomed Health Inform. 2025 Mar 28;PP. doi: 10.1109/JBHI.2025.3555813. Online ahead of print.

ABSTRACT

Electroencephalography (EEG) data is easily contaminated by various sources, significantly affecting subsequent analyses in neuroscience and clinical applications. Therefore, effective artifact removal is a key step in EEG preprocessing. While current deep learning methods have demonstrated notable efficacy in EEG denoising, single-channel approaches primarily focus on temporal features and neglect inter-channel correlations. Meanwhile, multi-channel methods mainly prioritize spatial features but often overlook the unique temporal dependencies of individual channels. A common limitation of both single-channel and multi-channel methods is their strict requirements on the input channel setting, which restricts their practical applicability. To address these issues, we design a flexible architecture named Artifact removal Spatio-Temporal Integration Network (ASTI-Net), a dual-branch denoising model capable of handling arbitrary EEG channel settings. ASTI-Net utilizes spatio-temporal attention weighting with dual branches that capture inter-channel spatial characteristics and intra-channel temporal dependencies. Its architecture incorporates deformable convolutional operations and channel-wise temporal processing, accommodating varying numbers of EEG channels and enhancing applicability across diverse clinical and research settings. By integrating features from both branches through a fusion reconstruction module, ASTI-Net effectively restores clean multi-channel EEG. Extensive evaluation on two semi-simulated datasets, along with qualitative assessment on real task-state EEG data, validates that ASTI-Net outperforms existing artifact removal methods.

PMID:40153283 | DOI:10.1109/JBHI.2025.3555813

IEEE J Biomed Health Inform. 2025 Mar 28;PP. doi: 10.1109/JBHI.2025.3555596. Online ahead of print.

ABSTRACT

The emergence of immune checkpoint inhibitors (ICIs) has significantly advanced cancer treatment. However, only 15-30% of the cancer patients respond to ICI treatment, which stimulates and enhances host immunity to eliminate tumor cells. ICI treatment is very expensive and has potential adverse reactions; therefore, it is crucial to develop a method which enables to accurately and rapidly assess a patient's suitability before ICI treatment. We complied germline whole-genome sequencing (WES) data of 37 melanoma patients who have been treated with ICIs and sequenced in our lab previously, and the WES data of other 700 ICI-treated cancer patients in public domain. Using these data, we proposed a novel double-channel attention neural network (DANN) model to predict cancer ICI-response and validate the predictions. DANN achieved a mean accuracy and AUC of 0.95 and 0.98, respectively, which outperformed traditional machine learning methods. Enrichment analysis of the DANN-identified genes indicated that cancer patients whose in-born genomic variants might mainly affect host immune system in a wide-ranging manner, and then affect ICI response. Finally, we found a set of 12 genes bearing genomic variants were significantly associated with cancer patient survivals after ICI treatment.

PMID:40153282 | DOI:10.1109/JBHI.2025.3555596

Mol Divers. 2025 Mar 28. doi: 10.1007/s11030-025-11173-y. Online ahead of print.

ABSTRACT

Antiviral peptides (AVPs) represent a novel and promising therapeutic alternative to conventional antiviral treatments, due to their broad-spectrum activity, high specificity, and low toxicity. The emergence of zoonotic viruses such as Zika, Ebola, and SARS-CoV-2 have accelerated AVP research, driven by advancements in data availability and artificial intelligence (AI). This review focuses on the development of AVP databases, their physicochemical properties, and predictive tools utilizing machine learning for AVP discovery. Machine learning plays a pivotal role in advancing and developing antiviral peptides and peptidomimetics, particularly through the development of specialized databases such as DRAVP, AVPdb, and DBAASP. These resources facilitate AVP characterization but face limitations, including small datasets, incomplete annotations, and inadequate integration with multi-omics data.The antiviral efficacy of AVPs is closely linked to their physicochemical properties, such as hydrophobicity and amphipathic α-helical structures, which enable viral membrane disruption and specific target interactions. Computational prediction tools employing machine learning and deep learning have significantly advanced AVP discovery. However, challenges like overfitting, limited experimental validation, and a lack of mechanistic insights hinder clinical translation.Future advancements should focus on improved validation frameworks, integration of in vivo data, and the development of interpretable models to elucidate AVP mechanisms. Expanding predictive models to address multi-target interactions and incorporating complex biological environments will be crucial for translating AVPs into effective clinical therapies.

PMID:40153158 | DOI:10.1007/s11030-025-11173-y

Skeletal Radiol. 2025 Mar 28. doi: 10.1007/s00256-025-04917-2. Online ahead of print.

ABSTRACT

OBJECTIVE: This study aims to establish a large degenerative cervical myelopathy cohort and develop deep learning models for predicting cervical canal stenosis from sagittal T2-weighted MRI.

MATERIALS AND METHODS: Data was collected retrospectively from patients who underwent a cervical spine MRI from January 2007 to December 2022 at a single institution. Ground truth labels for cervical canal stenosis were obtained from sagittal T2-weighted MRI using Kang's grade, a four-level scoring system that classifies stenosis with the degree of subarachnoid space obliteration and cord indentation. ResNet50, VGG16, MobileNetV3, and EfficientNetV2 were trained using threefold cross-validation, and the models exhibiting the largest area under the receiver operating characteristic curve (AUC) were selected to produce the ensemble model. Gradient-weighted class activation mapping was adopted for qualitative assessment. Models that incorporate demographic features were trained, and their corresponding AUCs on the test set were evaluated.

RESULTS: Of 8676 patients, 7645 were eligible for developing deep learning models, where 6880 (mean age, 56.0 ± 14.3 years, 3480 men) were used for training while 765 (mean age, 56.5 ± 14.4 years, 386 men) were set aside for testing. The ensemble model exhibited the largest AUC of 0.95 (0.94-0.97). Accuracy was 0.875 (0.851-0.898), sensitivity was 0.885 (0.855-0.915), and specificity was 0.861 (0.824-0.898). Qualitative analyses demonstrated that the models accurately pinpoint radiologic findings suggestive of cervical canal stenosis and myelopathy. Incorporation of demographic features did not result in a gain of AUC.

CONCLUSION: We have developed deep learning models from a large degenerative cervical myelopathy cohort and thoroughly explored their robustness and explainability.

PMID:40152984 | DOI:10.1007/s00256-025-04917-2

Am J Respir Crit Care Med. 2025 Mar 28. doi: 10.1164/rccm.202410-1934OC. Online ahead of print.

ABSTRACT

Rationale: Idiopathic pulmonary fibrosis (IPF) is characterized by excessive deposition of type 1 collagen. 68Ga-CBP8, a type 1 collagen positron emission tomography (PET) probe, measures collagen accumulation and shows higher collagen deposition in patients with IPF. Bexotegrast (PLN-74809) is an oral, once-daily, dual-selective inhibitor of αvβ6 and αvβ1 integrins under late-stage evaluation for treatment of IPF. Objectives: Evaluate changes in type 1 collagen in the lungs of participants with IPF following treatment with bexotegrast. Methods: In this Phase 2 (NCT05621252), single-center, double-blind, placebo-controlled study, adults with IPF received bexotegrast 160mg or placebo for 12 weeks. Primary endpoint was the change in whole-lung standardized uptake value (SUV) of 68Ga-CBP8 PET. Changes in lung dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) parameters, forced vital capacity (FVC), cough severity, and biomarkers of collagen synthesis and progressive disease were also assessed. Measurements and Main Results: Of 10 participants, 7 received bexotegrast and 3 placebo. At Week 12, mean change from baseline in top quartile of 68Ga-CBP8 whole-lung SUV was -1.2% with bexotegrast vs 6.6% with placebo; greatest mean changes were observed in subpleural lung regions in both groups (bexotegrast, -3.7%; placebo, 10.3%). DCE-MRI demonstrated numerically increased peak enhancement and faster contrast washout rate in bexotegrast-treated participants, suggesting improvements in lung microvasculature and decreased extravascular extracellular volume. Bexotegrast treatment resulted in numerical improvements in FVC, cough severity, and biomarker levels. Conclusions: The reduced uptake of 68Ga-CBP8 in the lungs of participants with IPF indicates an antifibrotic effect of bexotegrast, suggesting the potential for favorable lung remodeling.

PMID:40153543 | DOI:10.1164/rccm.202410-1934OC

Naunyn Schmiedebergs Arch Pharmacol. 2025 Mar 28. doi: 10.1007/s00210-025-04076-0. Online ahead of print.

ABSTRACT

The molecular link between endoplasmic reticulum stress (ERS) and idiopathic pulmonary fibrosis (IPF) remains elusive. Our study aimed to uncover core mechanisms and new therapeutic targets for IPF. By analyzing gene expression profiles from the Gene Expression Omnibus (GEO) database, we identified 1519 differentially expressed genes (DEGs) and 11 ERS-related genes (ERSRGs) diagnostic for IPF. Using weighted gene co-expression network analysis (WGCNA) and differential expression analysis, key genes linked to IPF were pinpointed. CIBERSORT was used to assess immune cell infiltration, while the Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed to explore biological mechanisms. In three GEO datasets (GSE150910, GSE92592, and GSE124685), the receiver operating characteristic (ROC) curve analysis showed area under the ROC curve (AUC) > 0.7 for all ERSRGs. The Connectivity Map (CMap) database was used to predict small molecules modulating IPF signatures. The molecular docking energies of mirdametinib with protein targets ranged from - 5.1643 to - 8.0154 kcal/mol, while those of linsitinib ranged from - 5.6031 to - 7.902 kcal/mol. Molecular docking and animal experiments were performed to validate the therapeutic potential of identified compounds, with mirdametinib showing specific effects in a murine bleomycin-induced pulmonary fibrosis model. In vitro experiments indicated that mirdametinib may alleviate pulmonary fibrosis by reducing ERS via the PI3K/Akt/mTOR pathway. Our findings highlight 11 ERSRGs as predictors of IPF and demonstrate the feasibility of bioinformatics in drug discovery for IPF treatment.

PMID:40153017 | DOI:10.1007/s00210-025-04076-0