Drug Deliv. 2025 Dec;32(1):2517137. doi: 10.1080/10717544.2025.2517137. Epub 2025 Jun 19.

ABSTRACT

Use of highly purified antigens to improve vaccine safety has led to reduced immunogenicity and efficacy, resulting in the need for adjuvants to increase and/or modulate the immunogenicity of the vaccine. Despite the need for potent and safe vaccine adjuvants, currently, there are still very few adjuvants in licensed human vaccines. Advances in immunology and molecular biology, especially in the last decade, have allowed researchers to understand better how the adjuvants work and enhance immune responses. While aluminum salts are still the most widely used adjuvants, research has shifted toward the rational design of adjuvant systems containing immunostimulatory molecules. Application of systems biology, which is based on high-throughput technologies using mathematical and computational modeling, has provided a deeper understanding of the biological events elicited by vaccination as well as the influence of other factors such as sex, age, microbiota, genetics and metabolism on the immune response. By this means, it became possible to tailor potential vaccine adjuvants more precisely for a successful vaccine with enhanced efficacy, safety and protection. In this review, after describing the mechanism of action of the adjuvants, current adjuvants in licensed vaccines, as well as those under clinical development will be mentioned in detail. Finally, new approaches in vaccine adjuvant development using systems biology and artificial intelligence will be reviewed, and future directions in vaccine research in regard to efficacy, safety and quality aspects will be discussed.

PMID:40536024 | DOI:10.1080/10717544.2025.2517137

R Soc Open Sci. 2025 Jun 18;12(6):241964. doi: 10.1098/rsos.241964. eCollection 2025 Jun.

ABSTRACT

During infectious disease outbreaks, humans often base their decision to adhere to an intervention strategy on individual choices and opinions. However, due to data limitations and inference challenges, infectious disease models usually omit these variables. We constructed a compartmental, deterministic Susceptible-Exposed-Infectious-Recovered (SEIR) disease model that includes a behavioural function with parameters influencing intervention uptake. The behavioural function accounted for an initial subpopulation opinion towards an intervention, their outbreak information awareness sensitivity and the extent to which they are swayed by the real-time intervention effectiveness information. Applying the model to vaccination uptake and three human pathogens-pandemic influenza, SARS-CoV-2 and Ebola virus-we explored through model simulation how these intervention adherence decision parameters and behavioural heterogeneity impacted epidemiological outcomes. From our model simulations, we found that in some pathogen systems, different types of outbreak information awareness at different outbreak stages may be more informative to an information-sensitive population and may lead to less severe epidemic outcomes. Incorporating behavioural functions that modify infection control intervention adherence into epidemiological models can aid our understanding of adherence dynamics during outbreaks. Ultimately, by parameterizing models with what we know about human behaviour towards vaccination adherence, such models can help assist decision-makers during outbreaks.

PMID:40535936 | PMC:PMC12173493 | DOI:10.1098/rsos.241964

MicroPubl Biol. 2025 May 30;2025. doi: 10.17912/micropub.biology.001666. eCollection 2025.

ABSTRACT

In the quantitative description of evolving phage-bacterial systems, a central challenge lies in accurately identifying the key parameters governing the dynamics of both bacterial and phage populations. This is especially relevant in the case of multidrug-resistant pathogenic bacteria such as Klebsiella sp . This pathogen poses serious health problems due to antibiotic overuse, which causes the emergence of antibiotic-resistant strains and great difficulty in eradicating bacterial infections with antibiotics. Research on phage-bacteria thus becomes a very important topic to provide alternative strategies to eradicate multidrug-resistant bacteria, and thus quantitative descriptions of these processes are of paramount importance. Despite increasing research on this topic, key structural parameters of the populations, such as bacterial growth rates, the impact of phages on bacterial dynamics or the probability of emergence of phage-resistant strains, are often scarce. In this study, we investigated a battery of growth experiments for Klebsiella pneumoniae alone and with the presence of bacteriophage vB_Kpn_2-P4. Using mathematical models we estimate key parameters for these experiments, showing the rapid growth and emergence of phage-resistant mutants which outcompete the susceptible bacteria strains. Our results provide quantitative estimates of these processes and may be useful for understanding phage-bacterial dynamical systems and parameterizing future theoretical and computational models.

PMID:40535529 | PMC:PMC12174997 | DOI:10.17912/micropub.biology.001666

Heliyon. 2025 Apr 2;11(9):e43282. doi: 10.1016/j.heliyon.2025.e43282. eCollection 2025 Apr.

ABSTRACT

[This retracts the article DOI: 10.1016/j.heliyon.2023.e15194.].

PMID:40535264 | PMC:PMC12134641 | DOI:10.1016/j.heliyon.2025.e43282

F1000Res. 2024 Sep 17;13:1061. doi: 10.12688/f1000research.156209.1. eCollection 2024.

ABSTRACT

Rab10 is a small GTPase involved in cargo transport from the trans-Golgi network to the plasma membrane and endocytic recycling back to the cell membrane. It has garnered significant interest in neurodegenerative disease research, particularly due to its phosphorylation by the LRRK2 kinase. This relationship underscores the importance of Rab10 in cellular processes related to disease pathology, specifically Parkinson's disease. The accessibility of renewable and selective antibodies against Rab10 would advance research efforts, enabling further understanding of its function and implications in disease. Here, we have characterized eight Rab10 commercial antibodies for western blot, immunoprecipitation, and immunofluorescence using a standardized experimental protocol based on comparing read-outs in knockout cell lines and isogenic parental controls. These studies are part of a larger, collaborative initiative seeking to address antibody reproducibility issues by characterizing commercially available antibodies for human proteins and publishing the results openly as a resource for the scientific community. While use of antibodies and protocols vary between laboratories, we encourage readers to use this report as a guide to select the most appropriate antibodies for their specific needs.

PMID:40535172 | PMC:PMC12174638 | DOI:10.12688/f1000research.156209.1

F1000Res. 2025 Jan 2;13:1049. doi: 10.12688/f1000research.155929.2. eCollection 2024.

ABSTRACT

Stimulator of interferon genes protein (STING1) is an immune adaptor protein which promotes innate immune defense mechanisms against pathogens. To enhance our understanding of STING1-associated disease, it is essential to make high-performing antibodies accessible to the scientific community. This study aims to improve reliability of STING1 research as we have characterized sixteen STING1 commercial antibodies for western blot, immunoprecipitation, and immunofluorescence using a standardized experimental protocol based on comparing read-outs in knockout cell lines and isogenic parental controls. These studies are part of a larger, collaborative initiative seeking to address antibody reproducibility issues by characterizing commercially available antibodies for human proteins and publishing the results openly as a resource for the scientific community. While use of antibodies and protocols vary between laboratories, we encourage readers to use this report as a guide to select the most appropriate antibodies for their specific needs.

PMID:40535171 | PMC:PMC12175898 | DOI:10.12688/f1000research.155929.2

Front Cardiovasc Med. 2025 Jun 4;12:1511415. doi: 10.3389/fcvm.2025.1511415. eCollection 2025.

ABSTRACT

BACKGROUND: Hypertrophic Cardiomyopathy (HCM) is an inherited heart disease and the pathogenesis of HCM involves genetic mutations, hemodynamic stress, and metabolic factors, with myocardial fibrosis playing a crucial role in severe clinical events. IL-33/ST2 signaling pathway known for its roles in immune response and tissue repair, participates in cardiac protection and anti-cardiac fibrosis in heart failure. The role of ST2 in HCM remains unclear, and IL-33/ST2 pathway and broader inflammatory responses may be critical in HCM.

METHODS: We re-analyzed RNA sequencing data from 9 high-throughput sequencing datasets comprising myocardial tissue samples from 109 HCM patients and 210 non-HCM controls. Differential gene expression analysis, correlation analyses, and Gene Set Enrichment Analysis (GSEA) were employed to explore the biological significance of ST2-related genes and the IL-33/ST2 pathway. Immune infiltration was assessed using CIBERSORTx, and protein-protein interaction networks were constructed using the STRING database.

RESULTS: Our analysis identified 2,660 upregulated and 403 downregulated genes for HCM in the combined dataset, with significant downregulation of the ST2 gene (log2 fold change = -5.0, adjusted P-value = 9.2 × 10-¹⁴³). This downregulation was consistently observed across multiple individual studies. Correlation analysis revealed significant positive correlations between ST2 and key inflammatory mediators such as IL6 and CD163. GSEA highlighted the enrichment of pathways related to immune response, inflammation, and cardiac morphogenesis, with notable upregulation of pro-inflammatory pathways. Immune infiltration analysis revealed a significant inverse correlation between ST2 expression and regulatory T cells (r = -0.34) and a positive correlation with neutrophils (r = 0.39). Pathway analysis indicated ST2's key role in networks involving inflammatory and fibrotic responses.

CONCLUSIONS: Our findings suggest that downregulation of ST2 in HCM may be associated with a dysregulated inflammatory gene network, potentially contributing to myocardial fibrosis and remodeling. These results highlight the possible critical role of the IL-33/ST2 pathway in disease progression, offering a potential therapeutic target for managing inflammation and fibrosis in HCM.

PMID:40535153 | PMC:PMC12174446 | DOI:10.3389/fcvm.2025.1511415

Comput Struct Biotechnol J. 2025 Jun 1;27:2434-2442. doi: 10.1016/j.csbj.2025.05.053. eCollection 2025.

ABSTRACT

A key obstacle in advancing acupuncture and moxibustion treatment (AMT) lies in the absence of effective methodologies capable of modeling the body's dynamic physiological changes and predicting treatment outcomes with quantitative precision. Colored Petri nets (CPNs), which have shown significant utility in simulating complex biological systems, offer a promising foundation for modeling AMT due to their capacity to represent hierarchical structures and dynamic behaviors. However, current modeling approaches struggle to address the inherent concurrency and complexity characteristic of AMT processes. To address this, we propose a novel token-guided transition control based on CPNs theory, enabling precise and efficient simulation of AMT systems. Furthermore, we develop a multicriteria evaluation method to quantitatively assess and compare the therapeutic efficacy of various AMT protocols, providing a structured approach for evidence-based decision-making. We validate our proposed model through simulation studies based on clinical cases of Meniere's disease. The simulation results closely align with actual clinical data, supporting the model's reliability and applicability. Finally, randomized simulation experiments have led to the identification of three new AMT strategies with promising therapeutic potential, highlighting the model's capacity to support treatment optimization and clinical innovation. This study introduces a comprehensive framework for dynamic modeling, visual representation, and quantitative evaluation of AMT systems. By offering a systematic and predictive approach to AMT analysis, the proposed method not only enhances understanding of treatment mechanisms but also contributes to the standardization of clinical practice.

PMID:40535109 | PMC:PMC12174566 | DOI:10.1016/j.csbj.2025.05.053

Phys Rev E. 2025 May;111(5-1):054412. doi: 10.1103/PhysRevE.111.054412.

ABSTRACT

The programming of computations in living cells is achieved by manipulating information flows within genetic networks. Typically, gene expression is discretized into high and low levels, representing 0 and 1 logic values to encode a single bit of information. However, molecular signaling and computation in living systems operate dynamically, stochastically, and continuously, challenging this binary paradigm. While stochastic and probabilistic models of computation address these complexities, there is a lack of work unifying these concepts to implement computations tailored to these features of living matter. Here we design genetic networks for stochastic and probabilistic computing, developing the underlying theory. Moving beyond the digital framework, we propose random pulses and probabilistic-bits (p-bits) as better candidates for encoding and processing information genetic networks. Encoding information through the frequency of expression burst frequency offers robustness to noise, while p-bits enable unique circuit designs with features like invertibility. We illustrate these advantages by designing circuits and providing mathematical models and simulations to demonstrate their functionality. Our approach to stochastic and probabilistic computing not only advances our understanding of information processing in biological systems but also opens new possibilities for designing genetic circuits with enhanced capabilities.

PMID:40534059 | DOI:10.1103/PhysRevE.111.054412

Phys Rev E. 2025 May;111(5-1):054113. doi: 10.1103/PhysRevE.111.054113.

ABSTRACT

We study the first-passage-time (FPT) properties of active Brownian particles to reach an absorbing wall in two dimensions. Employing a perturbation approach, we obtain exact analytical predictions for the survival and FPT distributions for small Péclet numbers, measuring the importance of self-propulsion relative to diffusion. While randomly oriented active agents reach the wall faster than their passive counterpart, their initial orientation plays a crucial role in the FPT statistics. Using the median as a metric, we quantify this anisotropy and find that it becomes more pronounced at distances where persistent active motion starts to dominate diffusion.

PMID:40533972 | DOI:10.1103/PhysRevE.111.054113

Ann Clin Transl Neurol. 2025 Jun 18. doi: 10.1002/acn3.70100. Online ahead of print.

ABSTRACT

OBJECTIVE: Dystonia is one of the most prevalent movement disorders, characterized by significant clinical and etiological heterogeneity. Despite considerable heritability (~25%), the etiology in most patients remains elusive. Moreover, understanding correlations between clinical manifestations and genetic variants has become increasingly complex.

METHODS: Exome sequencing was conducted on 1924 genetically unsolved, mainly late-onset isolated dystonia patients, recruited primarily from two dystonia registries (DysTract and the Dystonia Coalition). Rare variants in genes previously linked to dystonia (n = 406) were examined, confirmed via Sanger sequencing, and analyzed for segregation when possible.

RESULTS: We identified 137 distinct likely pathogenic/pathogenic variants (according to ACMG criteria) across 51 genes in 163/1924 patients, including 153/1895 index patients (diagnostic yield 8.1%). The strongest predictors of a genetic diagnosis were generalized dystonia (28.6% yield) and age at onset (20.4% yield in patients with onset < 30 years). Notably, 56.2% of these variants were novel, with recurrent variants in EIF2AK2, VPS16, KCNMA1, and SLC2A1. Additionally, 321 index patients (16.9%) harbored variants of uncertain significance in 102 genes. The most frequently implicated genes included VPS16, THAP1, GCH1, SGCE, GNAL, and KMT2B. Presumably pathogenic variants in less well-established dystonia genes were also found, including KCNMA1, KIF1A, and ZMYND11. At least six variants (in ADCY5, GNB1, IR2BPL, KCNN2, KMT2B, and VPS16) occurred de novo, supporting pathogenicity.

INTERPRETATION: This study provides valuable insights into the genetic landscape of dystonia, underscores the utility of exome sequencing for diagnosis, substantiates several candidate genes, and expands the phenotypic spectrum of some genes to include prominent, sometimes isolated dystonia.

PMID:40533913 | DOI:10.1002/acn3.70100

Microb Cell Fact. 2025 Jun 18;24(1):136. doi: 10.1186/s12934-025-02759-0.

NO ABSTRACT

PMID:40533732 | DOI:10.1186/s12934-025-02759-0

Nature. 2025 Jun 18. doi: 10.1038/s41586-025-09083-y. Online ahead of print.

ABSTRACT

Post-traumatic stress disorder (PTSD) is a polygenic disorder occurring after extreme trauma exposure. Recent studies have begun to detail the molecular biology of PTSD. However, given the array of PTSD-perturbed molecular pathways identified so far1, it is implausible that a single cell type is responsible. Here we profile the molecular responses in over two million nuclei from the dorsolateral prefrontal cortex of 111 human brains, collected post-mortem from individuals with and without PTSD and major depressive disorder. We identify neuronal and non-neuronal cell-type clusters, gene expression changes and transcriptional regulators, and map the epigenomic regulome of PTSD in a cell-type-specific manner. Our analysis revealed PTSD-associated gene alterations in inhibitory neurons, endothelial cells and microglia and uncovered genes and pathways associated with glucocorticoid signalling, GABAergic transmission and neuroinflammation. We further validated these findings using cell-type-specific spatial transcriptomics, confirming disruption of key genes such as SST and FKBP5. By integrating genetic, transcriptomic and epigenetic data, we uncovered the regulatory mechanisms of credible variants that disrupt PTSD genes, including ELFN1, MAD1L1 and KCNIP4, in a cell-type-specific context. Together, these findings provide a comprehensive characterization of the cell-specific molecular regulatory mechanisms that underlie the persisting effects of traumatic stress response on the human prefrontal cortex.

PMID:40533550 | DOI:10.1038/s41586-025-09083-y

Sci Data. 2025 Jun 18;12(1):1028. doi: 10.1038/s41597-025-05319-8.

ABSTRACT

We present 50 years of monitoring data on water quality of Lake Stechlin, a deep, dimictic hardwater lake in northeastern Germany known for its exceptionally clear water. Although located in a forested catchment, the lake has undergone major changes in recent decades, including a period of massive heating of surface water when receiving cooling water from a nearby nuclear power plant (1966-1990), accompanied by a greatly shortened water residence time from more than 40 years to less than 300 days. These changes are superimposed by a long-term trend of surface water warming and a concomitant decrease in winter ice cover. Total phosphorus concentrations have quadrupled since 2010 and zones of deep-water oxygen depletion have greatly expanded. The presented dataset covers basic water-chemical and physical records taken at monthly to fortnightly intervals from 1970 to 2020, documenting limnological changes during that period. Furthermore, it serves as a valuable basis to assess and project potential consequences of climate change and other types of environmental change on deep clearwater lakes in temperate climates.

PMID:40533475 | DOI:10.1038/s41597-025-05319-8

J Biol Chem. 2025 Jun 16:110368. doi: 10.1016/j.jbc.2025.110368. Online ahead of print.

ABSTRACT

Rather than inhibiting copper entry when grown on high Cu, yeast cells import excessive Cu while simultaneously increasing expression of metallothionein CUP1 which then sequesters the excess Cu. An ordinary-differential-equations-based kinetic model was developed to investigate this unusual behavior. The assumed reaction network included 25 reactions and 10 components in the cytosol of yeast cells growing in media supplemented with increasing nutrient COPPER concentrations. Published concentrations of copper proteins and coordination complexes that constitutes the low-molecular-mass (or labile) Cu pool were assumed. Other components included transcription factors MAC1 and ACE1, the MAC1-dependent copper importer CTR1, and other copper proteins considered collectively. A second MAC1-independent importer was required for sufficient Cu to enter the cell under Cu-excess conditions. The mathematical system was initially solved at steady-state for each condition in the series. The null-space of the stoichiometric matrix was evaluated using the Basic Pathways approach. Steady-state rates and rate-constants were calculated for each reaction and each condition of the series. Four rate-constants trended higher across the series indicating that the cell regulates those reactions in ways that were not included in the assumed rate-law expressions. This behavior was simulated by augmenting those expressions with logistical functions that sensed labile Cu and/or nutrient COPPER. The resulting integrated dynamical system approximately generated observed component concentrations over the series and was stable to both intracellular and extracellular perturbations. The MAC1-independent importer is predicted to be FET4, a nonspecific importer of both Cu and Fe. Cells likely tolerate excessive Cu import to import sufficient iron.

PMID:40533061 | DOI:10.1016/j.jbc.2025.110368

J Proteomics. 2025 Jun 16:105482. doi: 10.1016/j.jprot.2025.105482. Online ahead of print.

ABSTRACT

Melanoma remains the most aggressive form of skin cancer, characterized by high metastatic potential, genetic heterogeneity, and resistance to conventional therapies. The Melanoma MEGA-Study is a multi-center initiative designed to address these clinical challenges by integrating advanced proteogenomic profiling, clinical metadata, with AI-driven digital pathology and machine learning analytics, aiming to enhance personalized treatment strategies and improve patient outcomes. Between 2013 and 2022, a cohort of 1653 melanoma patients each contributed a primary tumor sample, with 361 providing 819 metastatic tumor samples. Clinical data collection for this cohort continued until May 2023. Comprehensive analyses using high-resolution mass spectrometry, optimized workflows for formalin-fixed paraffin-embedded tissues, and advanced digital pathology platforms enabled precise mapping of the tumor microenvironment, identification of metabolic reprogramming, and characterization of immune evasion signatures. The European Cancer Moonshot Lund Center's MEGA-Study, under the academic umbrella of Lund and Szeged universities, marks a significant advancement in its collaborative efforts with the National Institutes of Health (NIH) under the Cancer Moonshot partnership. This initiative exemplifies the center's dedication to pioneering cancer research and underscores the strength of its international collaborations. SIGNIFICANCE: The significance of this study lies in its pioneering integration of high-resolution proteomics, AI-driven digital pathology, and comprehensive clinical annotation to unravel the complex molecular landscape of melanoma. By leveraging a robust, population-based cohort of 1653 patients, including extensive analyses of both primary and metastatic tumor specimens, our approach provides unprecedented insights into the proteogenomic alterations that underpin tumor progression, immune evasion, and therapeutic resistance. The preliminary application of advanced mass spectrometry techniques to formalin-fixed paraffin-embedded tissues, combined with state-of-the-art digital pathology and machine learning, has enabled the identification of novel protein biomarkers and metabolic signatures that hold promise for refining patient stratification and informing personalized treatment strategies. This integrative framework not only deepens our understanding of melanoma biology but also establishes a scalable model for precision oncology that can be extended to other complex malignancies. Ultimately, our findings have the potential to transform clinical practice by facilitating earlier risk stratification, improving prognostication, and guiding the development of targeted therapeutic interventions for this highly aggressive cancer.

PMID:40532957 | DOI:10.1016/j.jprot.2025.105482

Br J Pharmacol. 2025 Jun 18. doi: 10.1111/bph.70106. Online ahead of print.

ABSTRACT

BACKGROUND AND PURPOSE: Hidden cardiotoxicity is defined as drug-induced cardiotoxicity that becomes obvious only in the presence of comorbidities. However, the molecular mechanisms of hidden cardiotoxicity are not always known. Therefore, unbiased multi-omics approaches could assist in revealing regulatory pathways. The most notable representative of hidden cardiotoxic drugs is the cyclooxygenase-2-inhibitor, rofecoxib. We previously reported increased mortality in rats because of proarrhythmic effects of rofecoxib in ischaemic hearts. Here, we aimed to identify molecular mechanisms of hidden cardiotoxicity exemplified by rofecoxib that present prior to comorbidities.

EXPERIMENTAL APPROACH: Rats were treated with rofecoxib or its vehicle for 4 weeks. RNA sequencing and proteomic datasets of heart samples were used for differential expression and pathway reconstruction analyses.

KEY RESULTS: In this model, mechanisms of hidden cardiotoxicity could not be revealed by transcriptomic analyses. However, mass-spectrometry-based proteomics showed conspicuous changes, revealing 132 proteins that were dysregulated in expression or on phosphorylation sites. Importantly, the phospho-proteomics allowed us to identify two kinases that may mediate cardiotoxicity. Finally, pathway reconstruction maps a complex molecular machinery whose clustered proteins regulate processes involving cytoskeleton binding, mRNA processing, proteolysis, translation, citrate acid cycle and calcium ion signalling.

CONCLUSION AND IMPLICATIONS: This is the first demonstration that multi-omics characterisation can reveal underlying regulatory pathways of hidden cardiotoxicity. Importantly, our study shows that transcriptomics gives limited information on the hidden cardiotoxic effects of rofecoxib, which are mainly mediated by changes in posttranslational modifications and protein expression. These changes, among other mechanisms, may disturb the cardiac calcium handling, which could explain the fatal arrhythmias following ischaemia/reperfusion observed with rofecoxib.

PMID:40532721 | DOI:10.1111/bph.70106

Immunity. 2025 Jun 11:S1074-7613(25)00241-9. doi: 10.1016/j.immuni.2025.05.020. Online ahead of print.

ABSTRACT

Older age, being male, obesity, smoking, and comorbidities (e.g., diabetes, asthma) are associated with an increased risk for severe infections. We hypothesized that there is a conserved common immune dysregulation across these risk factors. We integrated single-cell and bulk transcriptomic data and proteomic data from 12,026 blood samples across 68 cohorts to test this hypothesis. We found that our previously described 42-gene Severe-or-Mild (SoM) signature was associated with each of these risk factors prior to infection. Furthermore, this conserved immune signature was modifiable using immunomodulatory drugs and lifestyle changes. The SoM score predicted the individuals with sepsis who would be harmed by hydrocortisone treatment and individuals with asthma who would not respond to monoclonal antibody treatment. Finally, the SoM score was associated with all-cause mortality. The SoM signature has the potential to redefine the immunologic framing of the baseline immune state and response to chronic, subacute, and acute illnesses.

PMID:40532705 | DOI:10.1016/j.immuni.2025.05.020

Comput Biol Chem. 2025 Jun 11;119:108546. doi: 10.1016/j.compbiolchem.2025.108546. Online ahead of print.

ABSTRACT

Pre-eclampsia (PE) remains one of the leading causes of maternal and fetal morbidity, affecting 2-8 % of pregnancies worldwide. Despite great efforts in research, the precise molecular mechanisms underlying this complex disorder have not been identified. In this study, we used RNA sequence data (RNA-Seq) and applied advanced bioinformatics approaches to study the pathophysiology of PE. The weighted gene co-expression network analysis (WGCNA) method was used to construct a co-expression network of 239 differentially expressed genes (DEGs) between healthy and PE, which led to the identification of seven specific modules. Two modules, turquoise and yellow, showed strong co-relationships with PE. Further, functional enrichment pointed toward various important biological pathways, such as NAD metabolism, HIF-1 signaling, glycolysis/gluconeogenesis, PI3K AKT-signaling pathway, and JAK-STAT pathway. Further candidate genes were identified through clustering and analysis of protein interaction networks, and least absolute shrinkage and selection operator (LASSO) regression analyses identified five crucial predictor genes, such as GAPDH, LEP, PKM, TRIM24, and NDRG1, which are highly essential in PE. The prognostic potential of the identified biomarkers was confirmed by a receiver operating characteristic (ROC) curve analysis that achieved an area under the curve (AUC) of 0.987 and demonstrated high discriminatory power between the groups of healthy subjects and PE. To validate these findings, external validation was performed using microarray dataset. In addition, drug-gene interaction analyses were performed using the drug gene interaction database (DGIdb) database and revealed interactions for only three biomarkers: GAPDH, PKM, and LEP. These integrated systems biology approaches have identified key biomarkers and potential therapeutic targets for PE, providing a strong basis for future research into its molecular mechanisms and clinical management.

PMID:40532551 | DOI:10.1016/j.compbiolchem.2025.108546

Curr Opin Cell Biol. 2025 Jun 17;95:102563. doi: 10.1016/j.ceb.2025.102563. Online ahead of print.

ABSTRACT

Macropinocytosis is a conserved pathway for non-selective bulk uptake of extracellular fluid. It plays important roles in various cellular processes, including nutrient acquisition in Dictyostelium and cancer cells and antigen sampling by immune cells. This process is initiated by localized actin polymerization, which drives the formation of membrane protrusions that close to generate macropinosomes. Once formed, macropinosomes undergo maturation and traffic through the endolysosomal system for cargo degradation, whereas non-degradable material is exocytosed. Recent studies have uncovered conserved regulatory networks controlling macropinosome formation and maturation. This review provides an overview of these pathways, highlighting key molecular regulators and their coordinated responses to environmental signals. We also examine the interplay between macropinocytosis and cell migration, discussing potential mechanisms that balance these processes to optimize cellular function.

PMID:40532442 | DOI:10.1016/j.ceb.2025.102563