Nat Neurosci. 2025 Mar 31. doi: 10.1038/s41593-025-01905-6. Online ahead of print.

ABSTRACT

Natural spoken communication happens instantaneously. Speech delays longer than a few seconds can disrupt the natural flow of conversation. This makes it difficult for individuals with paralysis to participate in meaningful dialogue, potentially leading to feelings of isolation and frustration. Here we used high-density surface recordings of the speech sensorimotor cortex in a clinical trial participant with severe paralysis and anarthria to drive a continuously streaming naturalistic speech synthesizer. We designed and used deep learning recurrent neural network transducer models to achieve online large-vocabulary intelligible fluent speech synthesis personalized to the participant's preinjury voice with neural decoding in 80-ms increments. Offline, the models demonstrated implicit speech detection capabilities and could continuously decode speech indefinitely, enabling uninterrupted use of the decoder and further increasing speed. Our framework also successfully generalized to other silent-speech interfaces, including single-unit recordings and electromyography. Our findings introduce a speech-neuroprosthetic paradigm to restore naturalistic spoken communication to people with paralysis.

PMID:40164740 | DOI:10.1038/s41593-025-01905-6

Sci Rep. 2025 Mar 31;15(1):11006. doi: 10.1038/s41598-025-95267-5.

ABSTRACT

Prostate cancer (PCa) diagnosis faces significant challenges due to its complex pathological characteristics and insufficient pathologist resources. While deep learning-based image analysis (DLIA) shows promise in enhancing diagnostic accuracy, its application to radical prostatectomy (RP) specimens remains underexplored. In this study, we evaluated the clinical feasibility and prognostic value of a DLIA algorithm for Gleason grading and tumor quantification on whole RP specimens. Using 29,646 digitized H&E-stained slides from 992 patients who underwent RP, we compared the case-level algorithm results with pathologist assessments for the International Society of Urological Pathology grade groups (GG), tumor volumes (TV), and percent tumor volumes (PTV). We also evaluated their prognostic performance in predicting biochemical progression-free survival (BPFS). Pathologists identified cancer in 986 cases and assigned GG in 980, while the DLIA algorithm identified cancer and assigned GG to all cases without omission. DLIA-assigned GG showed fair concordance with pathologist assessments (linear-weighted Cohen's kappa: 0.374) and demonstrated similar efficacy in predicting BPFS (c-index: 0.644 for DLIA vs. 0.654 for pathologists; p = 0.52). In tumor quantification, DLIA-measured TV and PTV were strongly correlated with pathologist-based measurements (Pearson's correlation coefficient: 0.830 and 0.846, respectively), but showed stronger efficacy in BPFS prediction, with c-index values of 0.657 and 0.672 compared to 0.622 and 0.641, respectively. Incorporating DLIA-derived PTV into the CAPRA-S score significantly improved its predictive accuracy for BCR (p = 0.006), increasing the c-index from 0.704 to 0.715. Our findings indicate that DLIA algorithms can enhance the accuracy of Gleason grading and tumor quantification in RP specimens, providing valuable support in clinical decision-making for PCa management.

PMID:40164701 | DOI:10.1038/s41598-025-95267-5

Mol Psychiatry. 2025 Mar 31. doi: 10.1038/s41380-025-02974-6. Online ahead of print.

ABSTRACT

Major depressive disorder (MDD) presents a substantial health burden with low treatment response rates. Predicting antidepressant efficacy is challenging due to MDD's complex and varied neuropathology. Identifying biomarkers for antidepressant treatment requires thorough analysis of clinical trial data. Multimodal neuroimaging, combined with advanced data-driven methods, can enhance our understanding of the neurobiological processes influencing treatment outcomes. To address this, we analyzed resting-state fMRI and EEG connectivity data from 130 patients treated with sertraline and 135 patients with placebo from the Establishing Moderators and Biosignatures of Antidepressant Response in Clinical Care (EMBARC) study. A deep learning framework was developed using graph neural networks to integrate data-augmented connectivity and cross-modality correlation, aiming to predict individual symptom changes by revealing multimodal brain network signatures. The results showed that our model demonstrated promising prediction accuracy, with an R2 value of 0.24 for sertraline and 0.20 for placebo. It also exhibited potential in transferring predictions using only EEG. Key brain regions identified for predicting sertraline response included the inferior temporal gyrus (fMRI) and posterior cingulate cortex (EEG), while for placebo response, the precuneus (fMRI) and supplementary motor area (EEG) were critical. Additionally, both modalities identified the superior temporal gyrus and posterior cingulate cortex as significant for sertraline response, while the anterior cingulate cortex and postcentral gyrus were common predictors in the placebo arm. Additionally, variations in the frontoparietal control, ventral attention, dorsal attention, and limbic networks were notably associated with MDD treatment. By integrating fMRI and EEG, our study established novel multimodal brain network signatures to predict individual responses to sertraline and placebo in MDD, providing interpretable neural circuit patterns that may guide future targeted interventions. Trial Registration: Establishing Moderators and Biosignatures of Antidepressant Response for Clinical Care for Depression (EMBARC) ClinicalTrials.gov Identifier: NCT#01407094.

PMID:40164695 | DOI:10.1038/s41380-025-02974-6

Sci Rep. 2025 Mar 31;15(1):11000. doi: 10.1038/s41598-025-95709-0.

ABSTRACT

Well log analysis is significant for hydrocarbon exploration, providing detailed insights into subsurface geological formations. However, gaps and inaccuracies in well log data, often due to equipment limitations, operational challenges, and harsh subsurface conditions, can introduce significant uncertainties in reservoir evaluation. Addressing these challenges requires effective methods for both synthetic data generation and precise imputation of missing data, ensuring data completeness and reliability. This study introduces a novel framework utilizing sequence-based generative adversarial networks (GANs) specifically designed for well log data generation and imputation. The framework integrates two distinct sequence-based GAN models: time series GAN (TSGAN) for generating synthetic well log data and sequence GAN (SeqGAN) for imputing missing data. Both models were tested on a dataset from the North Sea, Netherlands region. For the imputation task, the input comprises logs with missing values and the output is the corresponding imputed logs; for the synthetic data generation task, the input is complete real logs and the output is synthetic logs that mimic the statistical properties of the original data. All log measurements are normalized to a 0-1 range using min-max scaling, and error metrics are reported in these normalized units. Different sections of 5, 10, and 50 data points were used. Experimental results demonstrate that this approach achieves superior accuracy in filling data gaps compared to other deep learning models for spatial series analysis. The imputation method yielded [Formula: see text] values of 0.92, 0.86, and 0.57, with corresponding mean absolute percentage error (MAPE) values of 8.320, 0.005, and 166.6, and mean absolute error (MAE) values of 0.012, 0.002, and 0.03, respectively. The synthetic generation yielded [Formula: see text] of 0.92, MAE, of 0.35, and MRLE of 0.01. These results set a new benchmark for data integrity and utility in geosciences, particularly in well log data analysis.

PMID:40164658 | DOI:10.1038/s41598-025-95709-0

Plant Genome. 2025 Jun;18(2):e70019. doi: 10.1002/tpg2.70019.

ABSTRACT

Groundnut (Arachis hypogaea L.), also known as peanut, is an allotetraploid legume crop composed of two different progenitor sub-genomes. This crop is an important source for food, feed, and confectioneries. Leveraging translational genomics research has expedited the precision and speed in making selections of progenies in several crops through either marker-assisted selection or genomic selection, including groundnut. The availability of foundational genomic resources such as reference genomes for diploid progenitors and cultivated tetraploids, offered substantial opportunities for genomic interventions, including the development of genotyping assays. Here, a cost-effective and high-throughput genotyping assay has been developed with 5,081 single nucleotide polymorphisms (SNPs) referred to as "mid-density assay." This multi-purpose assay includes 5,000 highly informative SNPs selected based on higher polymorphism information content (PIC) from our previously developed high-density "Axiom_Arachis" array containing 58,233 SNPs. Additionally 82 SNPs associated with five resilience and quality traits were included for marker-assisted selection. To test the utility of the mid-density genotyping (MDG) assay, 2,573 genotypes from distinct sets of breeding populations were genotyped with the 5,081 SNPs. PIC of the SNPs in the MDG ranged from 0.34 to 0.37 among diverse sets. The first three principal components collectively explained 82.08% of the variance among these genotypes. The mid-density assay demonstrated a proficient ability to distinguish between the genotypes, offering a high level of genome-wide nucleotide diversity. This assay holds promise for possible deployment in the identification of varietal seed mixtures, genetic purity within gene bank germplasms and seed systems, foreground and background selection in backcross breeding programs, genomic selection, and sparse trait mapping studies in groundnut.

PMID:40164965 | DOI:10.1002/tpg2.70019

Nat Methods. 2025 Mar 31. doi: 10.1038/s41592-025-02643-0. Online ahead of print.

ABSTRACT

Data from the first phase of the Human Tumor Atlas Network (HTAN) are now available, comprising 8,425 biospecimens from 2,042 research participants profiled with more than 20 molecular assays. The data were generated to study the evolution from precancerous to advanced disease. The HTAN Data Coordinating Center (DCC) has enabled their dissemination and effective reuse. We describe the diverse datasets, how to access them, data standards, underlying infrastructure and governance approaches, and our methods to sustain community engagement. HTAN data can be accessed through the HTAN Portal, explored in visualization tools-including CellxGene, Minerva and cBioPortal-and analyzed in the cloud through the NCI Cancer Research Data Commons. Infrastructure was developed to enable data ingestion and dissemination through the Synapse platform. The HTAN DCC's flexible and modular approach to sharing complex cancer research data offers valuable insights to other data-coordination efforts and researchers looking to leverage HTAN data.

PMID:40164800 | DOI:10.1038/s41592-025-02643-0

Commun Biol. 2025 Mar 31;8(1):527. doi: 10.1038/s42003-025-07954-8.

ABSTRACT

Epigenomic mechanisms are critically involved in mediation of genetic and environmental factors that underlie cancer development. Histone modifications represent highly informative epigenomic marks that reveal activation and repression of gene activities and dysregulation of transcriptional control due to tumorigenesis. Here, we present a comprehensive epigenomic and transcriptomic mapping of 18 stage I and II tumor and 20 non-neoplastic tissues from non-small cell lung adenocarcinoma patients. Our profiling covers 5 histone marks including activating (H3K4me3, H3K4me1, and H3K27ac) and repressive (H3K27me3 and H3K9me3) marks and the transcriptome using only 20 mg of tissue per sample, enabled by low-input omic technologies. Using advanced integrative bioinformatic analysis, we uncover cancer-driving signaling cascade networks, changes in 3D genome modularity, differential expression and functionalities of transcription factors and noncoding RNAs. Many of these identified genes and regulatory molecules show no significant change in their expression or a single epigenomic modality, emphasizing the power of integrative multimodal and multiomic analysis using patient samples.

PMID:40164799 | DOI:10.1038/s42003-025-07954-8

Nat Genet. 2025 Mar 31. doi: 10.1038/s41588-025-02134-0. Online ahead of print.

ABSTRACT

Tobacco smoke, alone or combined with alcohol, is the predominant cause of head and neck cancer (HNC). We explore how tobacco exposure contributes to cancer development by mutational signature analysis of 265 whole-genome sequenced HNC samples from eight countries. Six tobacco-associated mutational signatures were detected, including some not previously reported. Differences in HNC incidence between countries corresponded with differences in mutation burdens of tobacco-associated signatures, consistent with the dominant role of tobacco in HNC causation. Differences were found in the burden of tobacco-associated signatures between anatomical subsites, suggesting that tissue-specific factors modulate mutagenesis. We identified an association between tobacco smoking and alcohol-related signatures, indicating a combined effect of these exposures. Tobacco smoking was associated with differences in the mutational spectra, repertoire of driver mutations in cancer genes and patterns of copy number change. Our results demonstrate the multiple pathways by which tobacco smoke can influence the evolution of cancer cell clones.

PMID:40164736 | DOI:10.1038/s41588-025-02134-0

Mol Psychiatry. 2025 Mar 31. doi: 10.1038/s41380-025-02973-7. Online ahead of print.

ABSTRACT

Alzheimer's disease (AD) is a progressive neurodegenerative disorder with a decade-long preclinical pathological period that can be divided into several stages. Emerging evidence has revealed that the microbiota-gut-brain axis plays an important role in AD pathology. However, the role of gut microbiota in different AD stages has not been well characterized. In this study, we performed fecal shotgun metagenomic analysis on a Chinese cohort with 476 participants across five stages of AD pathology to characterize stage-specific alterations in gut microbiota and evaluate their diagnostic potential. We discovered extensive gut dysbiosis that is associated with neuroinflammation and neurotransmitter dysregulation, with over 10% of microbial species and gene families showing significant alterations during AD progression. Furthermore, we demonstrated that microbial gene families exhibited strong diagnostic capabilities, evidenced by an average AUC of 0.80 in cross-validation and 0.75 in independent external validation. In the optimal model, the most discriminant gene families are primarily involved in the metabolism of carbohydrates, amino acids, energy, glycan and vitamins. We found that stage-specific microbial gene families in AD pathology could be validated by an in vitro gut simulator and were associated with specific genera. We also observed that the gut microbiota could affect the progression of cognitive decline in 5xFAD mice through fecal microbiota transplantation, which could be used for early intervention of AD. Our multi-stage large cohort metagenomic analysis demonstrates that alterations in gut microbiota occur from the very early stages of AD pathology, offering important etiological and diagnostic insights.

PMID:40164697 | DOI:10.1038/s41380-025-02973-7

Bioimpacts. 2024 Jun 26;15:29952. doi: 10.34172/bi.29952. eCollection 2025.

ABSTRACT

INTRODUCTION: Drug repurposing as a low-cost, time-saving, and often less risky strategy has been attractive for the treatment of coronavirus disease 2019 (COVID-19) during the pandemic. This trial aimed to evaluate the effectiveness of dolutegravir, an HIV-1 integrase inhibitor, in admitted patients with moderate COVID-19.

METHODS: This study was a randomized, double-blind, placebo-controlled clinical trial assessing the efficacy of dolutegravir in adults admitted to a hospital in Ghaemshahr, Mazandaran Province, Iran. Patients aged 18-80 years with early symptoms of moderate COVID-19, which was confirmed based on reverse transcription polymerase chain reaction (RT-PCR) and/or chest computed tomography (CT) scan, were considered to be included in this study. Patients were randomly assigned in a 1:1 ratio to receive 50 mg dolutegravir plus the standard treatment regimen or the same value of placebo plus the standard treatment regimen, daily for 7 days. The standard treatment regimen was remdesivir 200 mg on day 1 followed by 100 mg for five days or until discharge. The primary endpoint was recovery 10 days after the beginning of the study.

RESULTS: Between August 22 and October 23, 2021, of 120 patients who were enrolled, 93 patients were randomly assigned to receive 50 mg dolutegravir (n=46) or the placebo regimen (n=47). No significant difference was observed between the two intervention groups based on the obtained results including frequency of respiratory modes during the first five days of admission, respiratory rate, and O2 saturation during six time periods.

CONCLUSION: The results showed that in adult patients admitted to the hospital with moderate COVID-19, treatment with dolutegravir was not associated with improvement in clinical recovery. Larger randomized trials are required to provide more robust evidence about the effectiveness of dolutegravir.

PMID:40161930 | PMC:PMC11954744 | DOI:10.34172/bi.29952

Front Oncol. 2025 Mar 14;15:1519355. doi: 10.3389/fonc.2025.1519355. eCollection 2025.

ABSTRACT

The research and development of new anti-cancer drugs face challenges such as high costs, lengthy development cycles, and limited data on side effects. In contrast, the clinical safety and side effects of traditional drugs have been well established through long-term use. The development or repurposing of traditional drugs with potential applications in cancer treatment offers an economical, feasible, and promising strategy for new drug development. This article reviews the novel applications of traditional drugs in tumor immunotherapy, discussing how they can enhance tumor treatment efficacy through functional repositioning, while also reducing development time and costs. Recent advancements in cancer immunotherapy have revolutionized treatment options, but resistance to ICIs remains a significant challenge. Drug repurposing has emerged as a promising strategy to identify novel agents that can enhance the efficacy of immunotherapies by overcoming ICI resistance. A study suggests that drug repositioning has the potential to modulate immune cell activity or alter the tumor microenvironment, thereby circumventing the resistance mechanisms associated with immune checkpoint blockade. This approach provides a rapid and cost-effective pathway for identifying therapeutic candidates that can be quickly transitioned into clinical trials. To improve the effectiveness of tumor immunotherapy, it is crucial to explore systematic methods for identifying repurposed drug candidates. Methods such as high-throughput screening, computational drug repositioning, and bioinformatic analysis have been employed to efficiently identify potential candidates for cancer treatment. Furthermore, leveraging databases related to immunotherapy and drug repurposing can provide valuable resources for drug discovery and facilitate the identification of promising compounds. It focuses on the latest advancements in the use of antidiabetic drugs, antihypertensive agents, weight-loss medications, antifungal agents, and antiviral drugs in tumor immunotherapy, examining their mechanisms of action, clinical application prospects, and associated challenges. In this context, our aim is to explore these strategies and highlight their potential for expanding the therapeutic options available for cancer immunotherapy, providing valuable references for cancer research and treatment.

PMID:40161377 | PMC:PMC11949826 | DOI:10.3389/fonc.2025.1519355

AIMS Microbiol. 2025 Feb 5;11(1):126-149. doi: 10.3934/microbiol.2025007. eCollection 2025.

ABSTRACT

BACKGROUND: Drug repositioning has emerged as a promising strategy for assessing its antimicrobial efficacy in treating infectious diseases.

METHODS: Seventy-five samples were collected and investigated for the presence of Pseudomonas aeruginosa. Antibiotic resistance, hemolytic activity, twitching motility, and biofilm formation were assessed. lasI and lasR genes were detected using conventional PCR. Minimum inhibitory concentrations of paroxetine, fluoxetine, and levofloxacin were determined by broth micro-dilution. The fractional inhibitory concentration index was calculated to assess the interaction between fluoxetine/levofloxacin and paroxetine/levofloxacin combinations. Half the MIC values of the drugs were selected for inhibitory effect assessment for virulence factors. Antibacterial and healing effects of fluoxetine were investigated on 30 male albino rats using a digital camera, bacterial count, and histological examination.

RESULTS: Our 25 P. aeruginosa isolates were highly drug-resistant. 80%, 92%, and 80% of isolates were positive for twitching motility, hemolysis, and biofilm formation, respectively. 92% of isolates were positive for lasI gene and 96% for lasR gene. MICs of fluoxetine and paroxetine ranged from 32 to 512 µg/mL and MICs of levofloxacin ranged from 1 to 256 µg/mL. A synergistic outcome was observed in both combinations. Biofilm formation, twitching motility, and hemolysis were inhibited by paroxetine and fluoxetine in the majority of isolates. Fluoxetine/levofloxacin and paroxetine/levofloxacin combinations inhibited twitching motility, hemolysis, and biofilm formation in all isolates. Enhanced wound healing was observed in rats treated with fluoxetine and levofloxacin, with the fluoxetine/levofloxacin combination group demonstrating the most significant wound-healing effect. Bacterial count decreased in rats treated with levofloxacin, fluoxetine, and the levofloxacin/fluoxetine combination. Histological examination revealed higher wound healing in the levofloxacin-treated group than the fluoxetine group, and the combination treatment group displayed the fastest rate of wound healing.

CONCLUSIONS: Paroxetine and fluoxetine showed considerable antibacterial inhibitory effects against multi-drug resistant P. aeruginosa isolates. Fluoxetine showed significant improvement in anti-inflammatory effects and wound healing. To the best of our knowledge, this is the first Egyptian study to investigate the repurposing of paroxetine and fluoxetine as antibacterial agents. Further studies are needed to investigate their applicability as antibacterial agents as single agents or in combination with other antibiotics.

PMID:40161243 | PMC:PMC11950684 | DOI:10.3934/microbiol.2025007

Trop Biomed. 2025 Mar 1;42(1):10-14. doi: 10.47665/tb.42.1.002.

ABSTRACT

Typhoid is an acute febrile illness primarily caused by Salmonella enterica serotype typhi (S. Typhi) which could be challenging to diagnose in children, owing to its non-specific clinical signs and symptoms which may resemble other febrile illnesses. Here, we present a case of typhoid which was atypically presented as fever of unknown origin (FUO) in a two-year-old boy with underlying glucose-6-phosphate dehydrogenase (G6PD) deficiency. This child was initially diagnosed and managed as acute tonsillopharyngitis, however remained febrile despite medications. A series of investigations were performed and S. Typhi was isolated from the bone marrow culture after almost a month of admission. The antibiotic was started based on antibiotic susceptibility testing and he recovered well. Our case underscores the challenges of diagnosis establishment and clinical management of typhoid in paediatric patients who has underlying disease and emphasizes the importance of having high index of clinical suspicion to ascertain timely and proper diagnosis.

PMID:40163397 | DOI:10.47665/tb.42.1.002

Drug Metab Rev. 2025 Mar 31:1-18. doi: 10.1080/03602532.2025.2485055. Online ahead of print.

ABSTRACT

Paclitaxel is a widely used chemotherapeutic agent recognized for its efficacy against various malignancies. However, its clinical utility is often limited by paclitaxel-induced peripheral neuropathy (PIPN), a dose-dependent and debilitating side effect that significantly impacts patient quality of life. Genetic predisposition plays a critical role in individual susceptibility to PIPN, influencing both drug metabolism and neuropathic responses. This review examines the genetic basis of PIPN, focusing on polymorphisms in key genes associated with paclitaxel metabolism, transport, neuroinflammation, and neuronal signaling. Variants in CYP2C8, CYP3A4, and CYP2C9 affect drug metabolism, while polymorphisms in ABCB1 and SLCO1B1 influence drug transport. Genes involved in neuroinflammatory pathways (TNF-α, IL-6, IL-1β), peripheral nerve integrity (MAPT, TUBB2), and neuronal signaling (SCN9A) have also been implicated in PIPN susceptibility. Understanding genetic contributions to PIPN is essential for unraveling its pathophysiology and developing targeted interventions. Integrating genetic markers into clinical practice can facilitate personalized treatment strategies, minimizing PIPN risk and enhancing therapeutic outcomes. Further studies are needed to validate these findings across diverse populations and uncover novel genetic determinants.

PMID:40162869 | DOI:10.1080/03602532.2025.2485055

Pharmacogenomics. 2025 Mar 31:1-7. doi: 10.1080/14622416.2025.2478810. Online ahead of print.

ABSTRACT

OBJECTIVE: We aimed to identify the impact of CYP2C19 polymorphism testing on clinical outcomes in patients who have undergone carotid artery stenting (CAS).

METHODS: This was a single-center retrospective cohort study. CYP2C19 polymorphisms were identified based on the presence of two normal functional alleles in normal metabolizers (NMs), a normal functional allele and a nonfunctional allele in intermediate metabolizers and two nonfunctional alleles in poor metabolizers. Patients were recommended for the CYP2C19 polymorphism testing followed by the change in dual antithrombotic drugs (DAPT) at the discretion of the supervising physician. The primary clinical endpoint was stent thrombosis (ST). Logistic regression was used to evaluate the relative risk of clinical outcomes.

RESULTS: A total of 273 patients were included. The relative risk of ST was not reduced in patients who underwent CYP2C19 polymorphism testing than in patients without this test (3.1% vs. 3.9%, OR = 0.914, 95% CI = 0.218-3.841). The ST in NMs and non-NMs was 3.4% and 2.9%, respectively, and showing no reduction in NMs (OR = 1.145, 95% CI = 0.162-8.105). Changing DAPT did not reduce the relative risk of ST compared with non-changing (2.3% vs. 3.2%, OR = 1.604, 95% CI = 0.024-107.033).

CONCLUSIONS: CYP2C19 polymorphism was not related to stent thrombosis in patients with CAS.

PMID:40162622 | DOI:10.1080/14622416.2025.2478810

J Cell Mol Med. 2025 Apr;29(7):e70511. doi: 10.1111/jcmm.70511.

ABSTRACT

Valve interstitial cells (VICs) play a critical role in aortic valve calcification and angiogenic processes associated with calcific aortic valve stenosis (CAVS). Within the same valve, VICs from differently calcified regions can exhibit diverse phenotypic and functional properties. We hypothesised that VICs isolated from noncalcified (NC-VICs) and calcified (C-VICs) areas of human aortic valves possess distinct angiogenic characteristics. In this study, we isolated C-VICs and NC-VICs from 23 valves obtained after aortic valve replacement due to CAVS. Both VIC types exhibited similar phenotypes in culture, characterised by morphology, expression of mesenchymal/fibroblastic markers, proliferation and osteogenic differentiation. No significant differences were observed in the secretion of angiogenic factors, including VEGF-A, Ang-1, Ang-2, PlGF, bFGF between NC-VICs and C-VICs. However, when co-injected with endothelial colony-forming cells (ECFCs) into Matrigel implants in vivo in mice, implants containing NC-VICs showed significantly higher microvessel density compared to those with C-VICs (p < 0.001). Additionally, NC-VICs co-cultured with ECFCs expressed significantly higher levels of the perivascular markers αSMA and calponin compared to C-VICs (p < 0.001 and p < 0.05, respectively). In conclusion, our study reveals the heterogeneity in VIC plasticity within the aortic valve during CAVS. The diminished capacity of VICs from calcified areas to differentiate into perivascular cells suggests a loss of function as valve disease progresses. Furthermore, the ability of VICs to undergo perivascular differentiation may provide insights into valve homeostasis, angiogenesis and the exacerbation of calcification.

PMID:40159645 | DOI:10.1111/jcmm.70511

PLoS One. 2025 Mar 31;20(3):e0319710. doi: 10.1371/journal.pone.0319710. eCollection 2025.

ABSTRACT

Mycobacterium abscessus (MABS) is an emerging pathogen causing severe infections, particularly in cystic fibrosis (CF) patients. A prospective multicentre study included CF patients from four hospitals in Madrid between January 2022 and January 2024. Respiratory samples were collected, and MABS isolates were analysed to determine their antibiotic resistance profiles, growth dynamics, infection kinetics, intracellular behaviour, and pathogenicity. Intracellular bacterial growth and macrophage viability were evaluated through THP-1 cell infection experiments, with and without amikacin. Phenotypic susceptibility testing and genotypic susceptibility testing were also conducted. Among 148 patients, 28 MABS isolates were detected from 16 patients (10.8%), and the first isolate from each patient was analysed. Isolation was more prevalent in younger individuals (median age 24.4 vs. 28.4 years, p = 0.049), and most isolates (81.25%) were identified as M. abscessus subsp. abscessus (MABSa). MABS isolates exhibited high resistance rates (>85%) to doxycycline, tobramycin, ciprofloxacin, moxifloxacin (75%) and cotrimoxazole (56.3%). Amikacin resistance (18.8%) was higher than expected, and inducible (10/16 isolates) or acquired (1/16 isolate) macrolide resistance was found in 68.8% of strains. Phenotypic and genotypic testing results were fully concordant. Tigecycline demonstrated strong in vitro activity, and resistance to imipenem, linezolid, and cefoxitin remained low. Rough strains displayed lower optical density values in later growth stages, probably due to their increased aggregation. In THP-1 cell infection experiments, rough strains showed higher intracellular bacterial loads with statistically significant differences observed at 2 hours (both with and without amikacin) and at 72 hours (with amikacin) post infection. Notably, rough strains also exhibited a higher internalisation index and greater impact on THP-1 cell viability, especially in the absence of amikacin.

PMID:40163512 | DOI:10.1371/journal.pone.0319710

Ther Adv Respir Dis. 2025 Jan-Dec;19:17534666251323194. doi: 10.1177/17534666251323194. Epub 2025 Mar 31.

ABSTRACT

Over the past decade, major clinical advances have been made in the healthcare and therapeutic development for cystic fibrosis (CF), a lethal genetic disease caused by mutations in the gene encoding the CF transmembrane conductance regulator (CFTR) protein. CFTR modulators represent innovative treatments that directly target the primary defects in the mutated CFTR protein and have demonstrated significant clinical benefits for many people with CF (pwCF) who are eligible for these treatments. In particular, the triple combination therapy composed of elexacaftor, tezacaftor, and ivacaftor (ETI) has changed the CF therapeutic landscape by significantly improving lung function, quality of life, and predicted survival rates. Here, we provided a comprehensive summary of the impact of ETI on clinical outcomes and the need for further research on long-term efficacy, side effects, pregnancy, possible drug-drug interactions, and extra-pulmonary manifestations. Moreover, a significant number of pwCF are unresponsive to these drugs or cannot afford their high costs. We, therefore, discussed health inequity issues and alternative therapeutic strategies under development aiming to obtain effective therapies for all pwCF.

PMID:40163448 | DOI:10.1177/17534666251323194

Microbiol Spectr. 2025 Mar 31:e0214924. doi: 10.1128/spectrum.02149-24. Online ahead of print.

ABSTRACT

Pseudomonas aeruginosa is an opportunistic pathogen that can cause sinus infections and pneumonia in cystic fibrosis (CF) patients. Bacteriophage therapy is being investigated as a treatment for antibiotic-resistant P. aeruginosa infections. Although virulent bacteriophages have shown promise in treating P. aeruginosa infections, the development of bacteriophage-insensitive mutants (BIMs) in the presence of bacteriophages has been described. The aim of this study was to examine the genetic changes associated with the BIM phenotype. Biofilms of three genetically distinct P. aeruginosa strains, including PAO1 (ATCC 15692), and two clinical respiratory isolates (one CF and one non-CF) were grown for 7 days and treated with either a cocktail of four bacteriophages or a vehicle control for 7 consecutive days. BIMs isolated from the biofilms were detected by streak assays, and resistance to the phage cocktail was confirmed using spot test assays. Comparison of whole genome sequencing between the recovered BIMs and their respective vehicle control-treated phage-sensitive isolates revealed structural variants in two strains, and several small variants in all three strains. These variations involved a TonB-dependent outer membrane receptor in one strain, and mutations in lipopolysaccharide synthesis genes in two strains. Prophage deletion and induction were also noted in two strains, as well as mutations in several genes associated with virulence factors. Mutations in genes involved in susceptibility to conventional antibiotics were also identified in BIMs, with both decreased and increased antibiotic sensitivity to various antibiotics being observed. These findings may have implications for future applications of lytic phage therapy.IMPORTANCELytic bacteriophages are viruses that infect and kill bacteria and can be used to treat difficult-to-treat bacterial infections, including biofilm-associated infections and multidrug-resistant bacteria. Pseudomonas aeruginosa is a bacterium that can cause life-threatening infections. Lytic bacteriophage therapy has been trialed in the treatment of P. aeruginosa infections; however, sometimes bacteria develop resistance to the bacteriophages. This study sheds light on the genetic mechanisms of such resistance, and how this might be harnessed to restore the sensitivity of multidrug-resistant P. aeruginosa to conventional antibiotics.

PMID:40162801 | DOI:10.1128/spectrum.02149-24

bioRxiv [Preprint]. 2025 Mar 12:2025.03.12.642861. doi: 10.1101/2025.03.12.642861.

ABSTRACT

Pseudomonas aeruginosa and Staphylococcus aureus are primary bacterial pathogens isolated from the airways of cystic fibrosis patients. P. aeruginosa produces secondary metabolites that negatively impact the fitness of S. aureus, allowing P. aeruginosa to become the most prominent bacterium when the species are co-cultured. Some of these metabolites inhibit S. aureus respiration. SrrAB is a staphylococcal two-component regulatory system (TCRS) that responds to alterations in respiratory status and helps S. aureus transition between fermentative and respiratory metabolisms. We used P. aeruginosa mutant strains and chemical genetics to demonstrate that P. aeruginosa secondary metabolites, HQNO in particular, inhibit S. aureus respiration, resulting in modified SrrAB stimulation. Metabolomic analyses found that the ratio of NAD + to NADH increased upon prolonged culture with HQNO. Consistent with this, the activity of the Rex transcriptional regulator, which senses and responds to alterations in the NAD + / NADH ratio, had altered activity upon HQNO treatment. The presence of SrrAB increased fitness when cultured with HQNO and increased survival when challenged with P. aeruginosa. S. aureus strains with a decreased ability to maintain redox homeostasis via fermentation had decreased fitness when challenged with HQNO and decreased survival when challenged with P. aeruginosa . These findings led to a model wherein P. aeruginosa secreted HQNO inhibits S. aureus respiration, stimulating SrrAB, which promotes fitness and survival by increasing carbon flux through fermentative pathways to maintain redox homeostasis.

IMPORTANCE: Cystic fibrosis (CF) is a hereditary respiratory disease that predisposes patients to bacterial infections, primarily caused by Staphylococcus aureus and Pseudomonas aeruginosa . P. aeruginosa excreted secondary metabolites decrease S. aureus fitness during co-infection, ultimately eliminating it. The genetic mechanisms that S. aureus uses to detect and respond to these metabolites are unknown. The S. aureus SrrAB two-component regulatory system senses flux through respiratory pathways and increases transcription of genes utilized for adaption to low-respiration environments. This study demonstrates that SrrAB responds to the P. aeruginosa -produced respiratory toxin HQNO and responds by increasing fermentation increasing competition. This study describes interactions between these two bacterial pathogens, which could be exploited to decrease pathogen burden in individuals living with cystic fibrosis.

PMID:40161799 | PMC:PMC11952440 | DOI:10.1101/2025.03.12.642861