Nucleic Acids Res. 2025 Apr 10;53(7):gkaf280. doi: 10.1093/nar/gkaf280.

ABSTRACT

Nuclear actin mediates enhancer-dependent transcriptional regulation at compartment level, playing critical roles in 3D genome organization. In β-actin depleted cells, H3K27 acetylation is enhanced, directly affecting enhancer-dependent transcriptional regulation and gene expression changes during compartment-switching. Here, we report these mechanisms are influenced by the long non-coding RNA (lncRNA) Meg3. Bulk RNA-seq analysis and qPCR on wild-type (WT), heterozygous (HET), and β-actin knockout (KO) mouse embryonic fibroblasts (MEFs) show that β-actin depletion significantly alters expression of several lncRNAs, including Meg3. Results from ChIRP-seq, ChIRP-MS, and fRIP-qPCR revealed that in β-actin KO cells, Meg3 becomes enriched and binds to H3K27 acetylation marks within gene regulatory regions. By integrating RNA-seq, H3K27 acetylation ChIP-seq, ATAC-seq, and HiC-seq data through activity by contact (ABC) analysis, we discovered Meg3 binding disrupts promoter-enhancer interactions in β-actin KO cells. These results, combined with metabolomics in WT, HET, and β-actin KO MEFs, show Meg3 binding to regulatory regions at sites of increased H3K27 acetylation impairs the expression of genes involved in the synthesis of chondroitin, heparan, dermatan sulfate, and phospholipases. We propose that in β-actin KO cells Meg3 binds to H3K27 acetylation levels. This interferes with promoter-enhancer interactions, disrupts genome organization, and downregulates gene expression and key metabolic pathways.

PMID:40226914 | DOI:10.1093/nar/gkaf280

Pract Lab Med. 2025 Mar 21;45:e00464. doi: 10.1016/j.plabm.2025.e00464. eCollection 2025 Jul.

ABSTRACT

BACKGROUND: Hepatocellular carcinoma (HCC) is a significant global health challenge with complex molecular underpinnings. Recent advancements in understanding the role of non-coding RNAs (ncRNAs) and exosomes in cancer biology have opened new avenues for research into potential diagnostic and therapeutic strategies.

METHODS: This study utilized a comprehensive approach to analyze gene expression patterns and regulatory networks in HCC. We integrated RNA sequencing data gathered from both tissue samples and exosomes. The WGCNA and limma R packages were employed to construct co-expression networks and identify differentially expressed ncRNAs, including long non-coding RNAs (lncRNAs) and circular RNAs (circRNAs).

RESULTS: Our analysis demonstrated distinct expression profiles of various ncRNAs in HCC, revealing their intricate interactions with cancer-related genes. Key findings include the identification of a network of microRNAs that interact with selected lncRNAs and their potential roles as biomarkers. Moreover, exosomal RNA was shown to effectively reflect tissue-specific gene expression changes.

CONCLUSIONS: The results of this study highlight the significance of exosomal ncRNAs in the progression of liver cancer, suggesting their potential as both diagnostic biomarkers and therapeutic targets. Future research should focus on the functional implications of these ncRNAs to further elucidate their roles in HCC and explore their applications in clinical settings.

PMID:40226122 | PMC:PMC11992429 | DOI:10.1016/j.plabm.2025.e00464

Hum Mutat. 2024 Aug 29;2024:7377504. doi: 10.1155/2024/7377504. eCollection 2024.

ABSTRACT

GNE myopathy (GNEM) is a rare autosomal recessive disorder characterized by progressive skeletal muscle wasting starting in early adulthood. The prevalence of GNEM is estimated to range between one and nine cases per million individuals, but the accuracy of these estimates is limited by underdiagnosis, misdiagnosis, and bias introduced by founder allele frequencies. As GNEM is a recessive disorder, unaffected carriers of single damaging variants can be expected to be found in the healthy population, providing an alternative method for estimating prevalence. We aim to estimate the prevalence of GNEM using allele frequencies obtained from healthy population genetic databases. We performed a review to establish a complete list of all known pathogenic GNEM variants from both literature and variant databases. We then developed standardized filtering steps using in silico tools to predict the pathogenicity of unreported GNE variants of uncertain clinical significance and validated our pathogenicity inferences using Mendelian Approach to Variant Effect pRedICtion built in Keras (MAVERICK) and AlphaMissense. We calculated conservative and liberal disease prevalence estimates using allele frequencies from the Genome Aggregation Database (gnomAD) population database by employing methodologies based on the assumptions of the Hardy-Weinberg Equilibrium. We additionally calculated estimates for disease prevalence removing the contribution of unique variant combinations that either do not cause myopathy in humans or result in embryonic lethality. We present the most comprehensive list of reported pathogenic GNE variants to date, together with additional variants predicted as pathogenic by in silico methods. We provide additional pathogenicity scores for these variants using new pathogenicity prediction tools and present a set of estimates for GNEM prevalence based on the different assumptions. Our most conservative estimate suggested a prevalence of 18.46 cases per million, while our most liberal estimate places the prevalence at 95.42 cases per million. When accounting for variant severity, this range drops to 11.00-87.68 cases per million. Our findings indicate that the true global prevalence of GNEM is greater than previous predictions underscoring that this condition is considerably more widespread than previously believed.

PMID:40225917 | PMC:PMC11919241 | DOI:10.1155/2024/7377504

Bone Rep. 2025 Mar 24;25:101839. doi: 10.1016/j.bonr.2025.101839. eCollection 2025 Jun.

ABSTRACT

Genetic studies have revealed hundreds of loci associated with bone-related phenotypes, including bone mineral density (BMD) and fracture risk. However, translating discovered loci into effective new therapies remains challenging. We review success stories including PCSK9-related drugs in cardiovascular disease and evidence supporting the use of human genetics to guide drug discovery, while highlighting advances in artificial intelligence and machine learning with the potential to improve target discovery in skeletal biology. These strategies are poised to improve how we integrate diverse data types, from genetic and electronic health records data to single-cell profiles and knowledge graphs. Such emerging computational methods can position bone genomics for a future of more precise, effective treatments, ultimately improving the outcomes for patients with common and rare skeletal disorders.

PMID:40225702 | PMC:PMC11986539 | DOI:10.1016/j.bonr.2025.101839

Theranostics. 2025 Mar 21;15(10):4654-4672. doi: 10.7150/thno.111272. eCollection 2025.

ABSTRACT

Glia reactivity, neuroinflammation and excitotoxic neuronal death are central processes to ischemic stroke and neurodegenerative diseases, altogether a leading cause of death, disability, and dementia. Given the high incidence of these pathologies and the limited efficacy of current treatments, developing brain-protective therapies that target both neurons and glial cells is a priority. Truncated neurotrophin receptor TrkB-T1, a protein produced by these cell types, plays relevant roles in excitotoxicity and ischemia. We hypothesized that interactions mediated by isoform-specific TrkB-T1 sequences might contribute to neurotoxicity and/or reactive gliosis, thus representing potential therapeutic targets. Methods: We designed cell-penetrating peptides containing TrkB-T1 isoform-specific sequences to: 1) characterize peptide delivery into rat primary cortical cultures and mice brain cortex; 2) isolate and identify the isoform interactome in basal and in vitro excitotoxic conditions; 3) analyze peptide effects on neuroinflammation and neurotoxicity using primary cultures subjected to excitotoxicity or in vivo in a mouse model of ischemia. Results: We identify here the TrkB-T1-specific interactome, poorly described to date, and demonstrate that interference of these protein-protein interactions using brain-accessible TrkB-T1-derived peptides can reduce reactive gliosis and decrease excitotoxicity-induced damage in cellular and animal models of stroke, where treatment reduces the infarct volume in male and female mice. Conclusions: The crucial role of TrkB-T1 in modulating microglia and astrocyte reactivity indicates that isoform-derived peptides hold promise for the development of therapies for human stroke and other excitotoxicity-associated pathologies.

PMID:40225562 | PMC:PMC11984388 | DOI:10.7150/thno.111272

NAR Mol Med. 2025 Mar 28;2(2):ugaf010. doi: 10.1093/narmme/ugaf010. eCollection 2025 Apr.

ABSTRACT

Understanding how exercise improves whole-body insulin sensitivity (Si) involves complex molecular signaling. This study examines skeletal muscle gene expression changes related to Si, considering sex differences, exercise amount, and intensity to identify pharmacologic targets mimicking exercise benefits. Fifty-three participants from STRRIDE (Studies of Targeted Risk Reduction Interventions through Defined Exercise) I and II completed eight months of aerobic training. Gene expression was assessed via Affymetrix and Illumina technologies, and Si was measured using intravenous glucose tolerance tests. A novel discovery protocol integrating literature-derived and data-driven modeling identified causal pathways and direct transcriptional targets. In women, exercise amount primarily influenced transcription factor targets, which were generally inhibitory, while in men, exercise intensity drove activating targets. Common transcription factors included ATF1, CEBPA, BACH2, and STAT1. Si-related transcriptional targets included TACR3 and TMC7 for intensity-driven effects, and GRIN3B and EIF3B for amount-driven effects. Two key pathways mediating Si improvements were identified: estrogen signaling and protein kinase C (PKC) signaling, both converging on the epidermal growth factor receptor (EGFR) and other relevant targets. The molecular pathways underlying Si improvements varied by sex and exercise parameters, highlighting potential skeletal muscle-specific drug targets such as EGFR to replicate the metabolic benefits of exercise.

PMID:40225320 | PMC:PMC11992681 | DOI:10.1093/narmme/ugaf010

Life Metab. 2025 Feb 8;4(2):loaf004. doi: 10.1093/lifemeta/loaf004. eCollection 2025 Apr.

ABSTRACT

Intestinal farnesoid X receptor (FXR) antagonists have been proven to be efficacious in ameliorating metabolic diseases, particularly for the treatment of metabolic dysfunction-associated steatohepatitis (MASH). All the reported FXR antagonists target to the ligand-binding pocket (LBP) of the receptor, whereas antagonist acting on the non-LBP site of nuclear receptor (NR) is conceived as a promising strategy to discover novel FXR antagonist. Here, we have postulated the hypothesis of antagonizing FXR by disrupting the interaction between FXR and coactivators, and have successfully developed a series of macrocyclic peptides as FXR antagonists based on this premise. The cyclopeptide DC646 not only exhibits potent inhibitory activity of FXR, but also demonstrates a high degree of selectivity towards other NRs. Moreover, cyclopeptide DC646 has high potential therapeutic benefit for the treatment of MASH in an intestinal FXR-dependent manner, along with a commendable safety profile. Mechanistically, distinct from other known FXR antagonists, cyclopeptide DC646 specifically binds to the coactivator binding site of FXR, which can block the coactivator recruitment, reducing the circulation of intestine-derived ceramides to the liver, and promoting the release of glucagon-like peptide-1 (GLP-1). Overall, we identify a novel cyclopeptide that targets FXR-coactivator interaction, paving the way for a new approach to treating MASH with FXR antagonists.

PMID:40225300 | PMC:PMC11992618 | DOI:10.1093/lifemeta/loaf004

Iran J Biotechnol. 2024 Oct 1;22(4):e3927. doi: 10.30498/ijb.2024.459448.3927. eCollection 2024 Oct.

ABSTRACT

BACKGROUND: Human leukocyte antigens (HLAs) play a pivotal role in orchestrating the host's immune response, offering a promising avenue with reduced adverse effects compared to conventional treatments. Cancer immunotherapies use HLA class I molecules for T cells to recognize tumor antigens, emphasizing the importance of identifying peptides that bind effectively to HLAs. Computer modeling of HLA-peptide binding speeds up the search for immunogenic epitopes, which enhances the prospect of personalized medicine and targeted therapies. The Immune Epitope Database (IEDB) is a vital repository, housing curated immune epitope data and prediction tools for HLA-peptide binding. It can be challenging for immunologists to choose the best tool from the IEDB for predicting HLA-peptide binding. This has led to the creation of consensus-based methods that combine the results of several predictors. One of the major challenges in these methods is how to effectively integrate the results from multiple predictors.

OBJECTIVES: Previous consensus-based methods integrate at most three tools by relying on simple strategies, such as selecting prediction methods based on their proximity to HLA in training data. In this study, we introduce HLAPepBinder, a novel consensus approach using ensemble machine learning methods to predict HLA-peptide binding, addressing the challenges biologists face in model selection.

MATERIALS AND METHODS: The key contribution is the development of an automatic pipeline named HLAPepBinder that integrates the predictions of multiple models using a random forest approach. Unlike previous approaches, HLAPepBinder seamlessly integrates results from all nine predictors, providing a comprehensive and accurate predictive framework. By combining the strengths of these models, HLAPepBinder eliminates the need for manual model selection, providing a streamlined and reliable solution for biologists.

RESULTS: HLAPepBinder offers a practical and high-performing alternative for HLA-peptide binding predictions, outperforming both traditional methods and complex deep learning models. Compared to the recently introduced transformer-based model, TranspHLA, which requires substantial computational resources, HLAPepBinder demonstrates superior performance in both prediction accuracy and resource efficiency. Notably, it operates effectively in limited computational environments, making it accessible to researchers with minimal resources. The codes are available online at https://github.com/CBRC-lab/HLAPepBinder.

CONCLUSION: Our study introduces a novel ensemble-learning model designed to enhance the accuracy and efficiency of HLA-peptide binding predictions. Due to the lack of reliable negative data and the typical assumption of unknown interactions being negative, we focus on analyzing the unknown HLA-peptide bindings in the test set that our model predicts with 100% certainty as positive bindings. Using HLAPepBinder, we identify 26 HLA-peptide pairs with absolute prediction confidence. These predictions are validated through a multi-step pipeline involving literature review, BLAST sequence similarity analysis, and molecular docking studies. This comprehensive validation process highlights HLAPepBinder's ability to make accurate and reliable predictions, contributing significantly to advancements in immunotherapy and vaccine development.

PMID:40225296 | PMC:PMC11993240 | DOI:10.30498/ijb.2024.459448.3927

Iran J Biotechnol. 2024 Oct 1;22(4):e3817. doi: 10.30498/ijb.2024.421319.3817. eCollection 2024 Oct.

ABSTRACT

BACKGROUND: Clear cell renal cell carcinoma (ccRCC, KIRC) is the most prevalent subtype of RCC, and even with different available therapies, the average progression-free survival is worse. Therefore, the identification of new molecular targets could be helpful for its therapeutic purposes.

MATERIALS AND METHODS: We used the Cancer Genome Atlas to perform bioinformatic analyses for genes with possible tumor suppressor roles in KIRC.

OBJECTIVE: This research aims to identify new prognostic biomarkers and potential therapeutic targets for this type of cancer.

RESULTS: We identified 14 down-regulated genes in KIRC that had not previously been studied or poorly studied, with the majority of them impacted by increased promoter methylation. Eight genes showed shorter overall survival and worse prognosis, indicating their function as tumor suppressors, and six genes revealed good prognosis. From the 8 genes, C7ORF41 and CTXN3 revealed only downregulation in most cancers, proposing them as highly potential tumor suppressors. Among these 8 genes, the function of CTXN3 in cancers is unknown. Moreover, we identified the CWH43 gene as the major signature of KIRC. In addition, we found different genes as signatures of KIRC tumor stages and grades.

CONCLUSIONS: Our results may shed light on identifying KIRC pathogenesis and developing effective therapeutic targets for renal cancers, mainly KIRC.

PMID:40225292 | PMC:PMC11993239 | DOI:10.30498/ijb.2024.421319.3817

Front Plant Sci. 2025 Mar 28;16:1543168. doi: 10.3389/fpls.2025.1543168. eCollection 2025.

ABSTRACT

In plant cell walls, lignin, cellulose, and the hemicelluloses form intricate three-dimensional structures. Owing to its complexity, lignin often acts as a bottleneck for the efficient utilization of polysaccharide components as biochemicals and functional materials. A promising approach to mitigate and/or overcome lignin recalcitrance is the qualitative and quantitative modification of lignin by genetic engineering. Feruloyl-CoA 6'-hydroxylase (F6'H1) is a 2-oxoglutarate-dependent dioxygenase that catalyzes the conversion of feruloyl-CoA, one of the intermediates of the lignin biosynthetic pathway, into 6'-hydroxyferuloyl-CoA, the precursor of scopoletin (7-hydroxy-6-methoxycoumarin). In a previous study with Arabidopsis thaliana, we demonstrated that overexpression of F6'H1 under a xylem-preferential promoter led to scopoletin incorporation into the cell wall. This altered the chemical structure of lignin without affecting lignin content or saccharification efficiency. In the present study, the same F6'H1 construct was introduced into hybrid aspen (Populus tremula × tremuloides T89), a model woody plant, and its effects on plant morphology, lignin chemical structure, global gene expression, and phenolic metabolism were examined. The transgenic plants successfully overproduced scopoletin while exhibiting severe growth retardation, a phenotype not previously observed in Arabidopsis. Scopoletin accumulation was most pronounced in the secondary walls of tracheary elements and the compound middle lamella, with low levels in the fiber cell walls. Overexpression of F6'H1 also affected the metabolism of aromatics, including lignin precursors. Heteronuclear single-quantum coherence (HSQC) NMR spectroscopy revealed that scopoletin in cell walls was bound to lignin, leading to a reduction in lignin content and changes in its monomeric composition and molar mass distribution. Furthermore, the enzymatic saccharification efficiency of the transgenic cell walls was more than three times higher than that of the wild-type plants, even without pretreatment. Although addressing growth inhibition remains a priority, incorporating scopoletin into lignin demonstrates significant potential for improving woody biomass utilization.

PMID:40225026 | PMC:PMC11985793 | DOI:10.3389/fpls.2025.1543168

Indian J Hematol Blood Transfus. 2025 Apr;41(2):383-387. doi: 10.1007/s12288-024-01826-7. Epub 2024 Jul 30.

ABSTRACT

BACKGROUND: Acute erythroid leukemia (AEL) accounts for 3% to 5% of AML patients. We present a case of AEL with whole exome sequencing (WES) data.

CASE REPORT: A 25-year-old male presented with easy fatiguability and fever on & off for 6 months. Complete blood counts revealed anemia, leukocytosis and thrombocytopenia. Peripheral blood smear showed numerous nucleated RBCs ~600nRBCs/ 100WBCs and no blastsBone marrow aspirate smears were markedly hemodiluted. Bone marrow biopsy was hypercellular for age with marked erythroid hyperplasia and predominance of early erythroid precursors. On immunohistochemistry, Glycophorin was diffusely positive, E-cadherin highlighted the early erythroid precursors and CD34 was negative. Possibility of AEL was considered.Total 77 AEL associated genes were taken out for functional association studies. Mutations already described in literature for AEL noted in this case were EPOR, JAK2, TP53, GATA 2, NPM1 and WT1. Novel mutations found in this case were ERCC6L2, PYGO1 and MYH9The patient left the hospital against medical advice and expired within a month of diagnosis.

CONCLUSION: This case is interesting as AEL presented in a young male and PBS showed 600nRBCs/ 100 WBCs. Targeted sequencing can help to confirm the diagnosis of AEL especially in dilute marrows.

SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s12288-024-01826-7.

PMID:40224680 | PMC:PMC11992317 | DOI:10.1007/s12288-024-01826-7

Front Immunol. 2025 Mar 28;16:1539373. doi: 10.3389/fimmu.2025.1539373. eCollection 2025.

ABSTRACT

The use of immune checkpoint inhibitors (ICI) can lead to immune-related adverse events (irAE), of which skin irAE is common, affecting up to 50% of ICI-treated patients. Although only a few cases of subacute cutaneous lupus erythematosus (SCLE) have been reported in patients receiving anti-programmed death-1(anti-PD-1) immunotherapy, it is important to identify ICI-induced SCLE because it may cause delayed and/or prolonged skin reactions even after treatment discontinuation. To date, no cases of cutaneous lupus associated with Camrelizumab treatment have been reported.

CASE REPORT: We report a case of a patient with advanced non-small cell lung cancer (NSCLC) who gradually developed erythematous rashes on sun-exposed skin with pruritus after one course of anti-PD-1 antibody Camrelizumab combined with chemotherapy. The rashes were initially considered as eczema, but did not improve after symptomatic treatment. The rashes continued to worsen after the third course of treatment, and the pruritus was unbearable. After antibody testing, the patient was found to have positive anti-SS-A/Ro antibody, and the histological changes were consistent with subacute cutaneous lupus erythematosus. SCLE was controlled with local and systemic glucocorticoids, hydroxychloroquine, and discontinuation of anti-PD-1 therapy.

CONCLUSION: Camrelizumab treatment may be associated with the appearance of subacute cutaneous lupus erythematosus in sun-exposed skin regions, which can be rapidly relieved by local and systemic glucocorticoids and hydroxychloroquine. It is recommended to perform early antibody testing and skin biopsy for diagnosis and treatment. Unlike classic drug-related SCLE, patients may develop multiple autoimmune diseases, and caution should be taken when using immune checkpoint inhibitors for subsequent treatment.

PMID:40226630 | PMC:PMC11985835 | DOI:10.3389/fimmu.2025.1539373

Kidney Int Rep. 2024 Dec 6;10(3):720-729. doi: 10.1016/j.ekir.2024.12.002. eCollection 2025 Mar.

ABSTRACT

INTRODUCTION: Pegmolesatide has been recently approved for treating anemia in chronic kidney disease (CKD) patients in China. We presented the results of the pivotal study conducted in patients with nondialysis-dependent (NDD)-CKD with anemia.

METHODS: This randomized, active-controlled, open-label, noninferiority phase 3 study was conducted across 38 centers in China. Eligible patients were randomly assigned to receive subcutaneous injection of pegmolesatide in the upper arm once every 4 weeks or epoetin alfa weekly or biweekly, with doses adjusted to maintain hemoglobin (Hb) level of 100 to 120 g/l. The primary outcome was the mean change in Hb level from the baseline during the efficacy evaluation period. Noninferiority of pegmolesatide to epoetin alfa was established if the lower limit of the 2-sided 95% confidence interval (CI) was ≥ -10 g/l.

RESULTS: A total of 173 patients received at least 1 dose of pegmolesatide (115 patients) or epoetin alfa (58 patients). During the efficacy evaluation period, the mean change in Hb from baseline level was 19.2 g/l in the pegmolesatide group and 15.4 g/l in the epoetin alfa group with a between-group difference of 3.8 g/l (95% CI: 0.7-6.9). The incidence of adverse events (AEs) and serious AEs (SAEs) were similar between groups, with hypertension being the most reported AE related to the study drug. No drug-related hypersensitivity reactions or fatal events were observed.

CONCLUSION: Pegmolesatide demonstrated comparable efficacy to epoetin alfa in elevating and maintaining Hb levels in patients with NDD-CKD with anemia without new safety concerns (ClinicalTrials.gov identifier: NCT03903809).

PMID:40225393 | PMC:PMC11993201 | DOI:10.1016/j.ekir.2024.12.002

Front Pharmacol. 2025 Mar 28;16:1460338. doi: 10.3389/fphar.2025.1460338. eCollection 2025.

ABSTRACT

BACKGROUND: The influence of butylphthalide on atherosclerotic plaque burden remains underexplored. This pooled analysis was aimed to evaluate its efficacy and safety in carotid atherosclerosis.

METHODS: The literature were retrieved in online databases. Carotid intima-media thickness (IMT), plaque size, Crouse score, National Institute of Health Stroke Scale (NIHSS), circulating biomarkers, and drug-related adverse events were extracted and compared between the butylphthalide group and the control group without butylphthalide.

RESULTS: Nine randomized controlled trials with 892 subjects were included. Compared with the control group, butylphthalide significantly reduced carotid IMT (MD -0.24 mm, 95% CI [-0.31, -0.16], P < 0.00001), plaque size (MD -3.83 mm2, 95% CI [-5.64, -2.01], P < 0.0001), Crouse score (MD -0.48, 95% CI [-0.89, -0.08], P = 0.02), hs-CRP (MD -1.65 mg/L, 95% CI [-2.99, -0.30], P = 0.02) and MMP-9 (MD -12.29 μg/L, 95% CI [-16.24, -8.33], P < 0.00001). Neurological improvement (NIHSS reduction: MD -2.94, 95% CI [-4.15, -1.73], P < 0.00001) and comparable safety profiles (OR 0.93, 95% CI [0.37, 2.37], P = 0.89) were observed.

CONCLUSION: Butylphthalide treatment reduces carotid plaque burden, improves neurological recovery and has a high safety profile, supporting its role in stroke prevention.

PMID:40223926 | PMC:PMC11986422 | DOI:10.3389/fphar.2025.1460338

Proteomics. 2025 Apr 14:e202400241. doi: 10.1002/pmic.202400241. Online ahead of print.

ABSTRACT

Spaceflight poses unique challenges to human health due to exposure to increased levels of cosmic radiation, microgravity, and associated oxidative stress. These environmental factors can lead to cellular damage, inflammation, and a range of health complications, including cardiovascular problems, immune system impairment, and an increased risk of cancer. Nuclear factor erythroid 2-related factor 2 (NRF2) is a critical transcription factor that regulates the body's defense mechanisms against oxidative stress by promoting the expression of antioxidant enzymes. Recent research has shed more light on the critical role of NRF2 in addressing space-related health challenges. In this study, we developed a computational methodology to explore the plasticity of the gene expression profile in flight and postflight conditions, highlighting the genes and corresponding mechanisms that do not return to ground levels and correlate with gene signatures associated with cardiovascular disease (CVD). RNA sequencing (RNA-seq) data from human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) have been used to investigate the cellular effects of microgravity on cardiac function. Gene expression monotonicity studies were performed and linked to genome-wide association studies (GWAS) to highlight the monotonically expressed genes associated with CVD. The selected monotonically expressed genes were also mapped onto the NRF2 network to investigate the impact of spaceflight on human cardiomyocyte function in the context of redox signaling pathways. Based on this knowledge, we used computational drug repurposing methods to suggest a short list of repurposed drug candidates that can be further tested in astronauts for the prevention of CVD. This study provides insights into the molecular and redox signaling alterations in cardiomyocytes induced by spaceflight, laying the foundation for future research aimed at mitigating cardiovascular risks in astronauts and advancing clinical applications on Earth.

PMID:40223711 | DOI:10.1002/pmic.202400241

Expert Opin Drug Discov. 2025 Apr 14:1-10. doi: 10.1080/17460441.2025.2490251. Online ahead of print.

ABSTRACT

INTRODUCTION: The journey from initial drug discovery to approval for respiratory diseases typically spans approximately 10.4 years and cost over $2.8 billion. This intricate process involves five stages: target identification, therapeutic molecule discovery, preclinical testing, clinical trials, and regulatory approval.

AREAS COVERED: This review examines novel drug discovery strategies for chronic obstructive pulmonary disease (COPD), focusing on advanced in vitro models that replicate human lung conditions for accurate drug testing according to the following search string: discovery AND strategy AND COPD. It explores targeted molecular therapies, structure-based drug design, and drug repurposing approaches facilitated by computational analysis. The significance of personalized medicine in tailoring treatments for diverse COPDs is emphasized, highlighting the complexity of the disease and the necessity of these innovative methodologies to improve therapeutic outcomes.

EXPERT OPINION: COPD remains a challenging area, with a significant unmet medical need. Despite previous efforts, few effective therapies exist. Innovative in vitro models, targeted molecular therapies, and drug repurposing strategies are showing promise. Emphasizing advanced preclinical models and repurposing existing drugs could transform treatment paradigms, promoting more effective therapies for complex diseases like COPD. These innovations hold potential for enhancing drug discovery efficiency, leading to personalized and precision medicine approaches.

PMID:40223433 | DOI:10.1080/17460441.2025.2490251

Drug Test Anal. 2025 Apr 13. doi: 10.1002/dta.3887. Online ahead of print.

ABSTRACT

Pharmacological potential of Hypoxen, previously registered as Olifen is evaluated herein. Hypoxen is categorized as antihypoxic agent. The active substance is polydihydroxyphenylene thiosulfonate sodium. Human studies are limited and no clinical trials following international standards is available. There is however a developed body of knowledge emerging from original studies conducted by the Russian Military Medical Academy in 1980s and 1990s despite limited online access. Hypoxen is promoted to improve oxygen supply or reduce oxygen consumption under hypoxic conditions and physical load. It is thought to support faster recovery, and can be used in complex treatments of diseases accompanied by hypoxia like myocardial ischemia. From clinical perspective, it may enhance cellular respiration by improving coupling in the respiratory chain/accelerating oxidative phosphorylation, but also inhibit succinate dehydrogenase (SDH), and activate mitochondrial ATP-sensitive potassium channels (mitoKATP) in skeletal muscles and myocardium. In 2023, the World Anti-Doping Agency (WADA) added Hypoxen to the Monitoring Program as there had been documented evidence of its use by athletes. On in vitro experiments compared the influence of Hypoxen on oxidative phosphorylation with mitochondrial uncoupling agent 2,4-dinitrophenol (DNP) a unique metabolic modulator that strongly accelerates the metabolism rate, prohibited since 2024 by WADA. Most studies focus on exercise performance, and may provide some evidence that Hypoxen has the potential to enhance performance, the first criteria considered for addition of substance to the WADA Prohibited List. Pharmacodynamics and ergogenic effects of Hypoxen suggests potential as metabolic modulator.

PMID:40223246 | DOI:10.1002/dta.3887

Exp Clin Transplant. 2025 Mar;23(3):220-226. doi: 10.6002/ect.2024.0243.

ABSTRACT

OBJECTIVES: Lung transplant recipients are vulnerable to respiratory infections because of their compromised immune response. Limited research has been published on mental health as a result of the COVID-19 pandemic on lung transplant recipients, and uncertainty remains whether the COVID-19 vaccine affected mental health in lung transplant recipients.

MATERIALS AND METHODS: In this longitudinal, retrospective study, we assessed the psychosocial wellbeing of lung transplant recipients during the COVID-19 pandemic at 2 different time points (before and after COVID-19 vaccination). We measured wellbeing with the Hospital Anxiety and Depression Scale (cutoff of 11 points indicated anxiety and depression) and the Symptom Checklist consisting of 9 questions.

RESULTS: Our study included 83 patients (mean age 52.4 ± 14.5 years, 55.4% male). Among the patients, 3.8% and 4.8% of patients with cystic fibrosis had abnormal values for anxiety before and after the vaccine, respectively; abnormal values for depression were shown in 0% and 2.4% of patients with cystic fibrosis before and after the vaccine, respectively. Sex, age, level of education, time since transplant, and chronic allograft dysfunction were not significantly associated with psychosocial wellbeing. Vaccination against COVID-19 was not associated with a change in psychosocial wellbeing.

CONCLUSIONS: We found no evidence that the COVID-19 vaccine affected the psychosocial wellbeing of lung transplant recipients. However, it may be important to monitor wellbeing closely during a pandemic, especially in patients with cystic fibrosis.

PMID:40223386 | DOI:10.6002/ect.2024.0243

Eur J Ophthalmol. 2025 Apr 13:11206721251318384. doi: 10.1177/11206721251318384. Online ahead of print.

ABSTRACT

Refractive error is among the leading causes of visual impairment globally. The diagnosis and management of refractive error has traditionally relied on comprehensive eye examinations by eye care professionals, but access to these specialized services has remained limited in many areas of the world. Given this, artificial intelligence (AI) has shown immense potential in transforming the diagnosis and management of refractive error. We review AI applications across various aspects of refractive error care - from axial length prediction using fundus images to risk stratification for myopia progression. AI algorithms can be trained to analyze clinical data to detect refractive error as well as predict associated risks of myopia progression. For treatments such as implantable collamer and orthokeratology lenses, AI models facilitate vault size prediction and optimal lens fitting with high accuracy. Furthermore, AI has demonstrated promise in optimizing surgical planning and outcomes for refractive procedures. Emerging digital technologies such as telehealth, smartphone applications, and virtual reality integrated with AI present novel avenues for refractive error screening. We discuss key challenges, including limited validation datasets, lack of data standardization, image quality issues, population heterogeneity, practical deployment, and ethical considerations regarding patient privacy that need to be addressed before widespread clinical implementation.

PMID:40223314 | DOI:10.1177/11206721251318384

Respirology. 2025 Apr 13. doi: 10.1111/resp.70043. Online ahead of print.

ABSTRACT

BACKGROUND AND OBJECTIVE: Idiopathic pulmonary fibrosis is a progressive interstitial lung disease characterised by excessive activation of myofibroblasts. However, currently available antifibrotic drugs exhibit limited efficacy. The dysregulation of redox processes plays a significant role in the pathogenesis of idiopathic pulmonary fibrosis. Dextromethorphan (DM) is used in the treatment of various inflammation-related diseases. This study aimed to investigate the effectiveness of the combination of DM and pirfenidone (PFD) in treating idiopathic pulmonary fibrosis in both animal models and humans.

METHODS: In a bleomycin-induced pulmonary fibrosis mouse model, the anti-fibrotic effects of DM and/or PFD were assessed by evaluating fibrotic area, hydroxyproline levels, and fibrotic markers. In a transforming growth factor-β1-induced cell model, proliferation, migration, fibrosis markers, and oxidative stress were analysed to elucidate the mechanisms underlying the anti-fibrotic actions of DM and/or PFD. Finally, the efficacy of DM combined with PFD in patients with pulmonary fibrosis was evaluated by comparing pulmonary imaging scores and pulmonary function before and after treatment in the PFD group and the PFD + DM group.

RESULTS: We observed that even ultralow doses of DM, either alone or in combination with PFD, demonstrated substantial protective effects in mice. Notably, administration of DM or combined drugs at 2 weeks after bleomycin modelling still showed anti-fibrotic effects. In vitro, DM monotherapy and combination therapy restored the redox balance by suppressing nicotinamide adenine dinucleotide phosphate (NADPH) oxidase 4/reactive oxygen species production and upregulating superoxide dismutase, contributing to their anti-fibrotic mechanisms. In the clinical study, add-on DM improved PFD in mitigating pulmonary function decline and improving chest high-resolution computed tomography imaging scores.

CONCLUSIONS: Ultralow doses of dextromethorphan significantly alleviate pulmonary fibrosis in bleomycin-treated mice through restoring the redox balance. Add-on DM improves the effects of PFD in both bleomycin-treated mice and patients with pulmonary fibrosis.

TRIAL REGISTRATION: ChiCTR2000037602.

PMID:40223283 | DOI:10.1111/resp.70043