Biodivers Data J. 2025 Feb 6;13:e134717. doi: 10.3897/BDJ.12.e134717. eCollection 2025.

ABSTRACT

BACKGROUND: The section Cryptogamia-Lichenes of the Herbarium Universitatis Taurinensis (TO) includes ca. 34,600 lichen specimens, organised in the historical (ca. 30,700 specimens, mostly from the 19th century) and modern (ca. 3,900 specimens collected from 1978, out of which ca. 3400 from Italy) collections. Specimens from the administrative regions of Piemonte and Valle d'Aosta (NW Italy) are the core of the modern collection, documenting floristic and vegetation studies, as well as biomonitoring campaigns and investigations on the biodeterioration of the stone cultural heritage.

NEW INFORMATION: The dataset of the Italian materials of the modern lichenological collection of TO, with 3,365 samples, is fully georeferenced and accessible in the Global Biodiversity Information Facility (GBIF), in the Jointly Administered Herbarium Management System and Specimen Database (JACQ) and in the Information System of Italian Lichens (ITALIC). With regard to the historical collection, only a set of 59 recently revised specimens is available on the mentioned platforms, but most of the materials are accessible as digital images on the website of the project HERB-TO-CHANGE.

PMID:39958908 | PMC:PMC11826221 | DOI:10.3897/BDJ.12.e134717

Curr Res Microb Sci. 2025 Jan 23;8:100352. doi: 10.1016/j.crmicr.2025.100352. eCollection 2025.

ABSTRACT

A sustainable approach to microbial polyhydroxyalkanoate (PHA) production involves utilizing waste as a substrate, which can include toxic pollutants like phenol as a carbon feedstock. Phenol-contaminated effluents offer cost-effective and readily available resources for PHA production, while simultaneously addressing phenol contamination issues. Understanding the metabolic conversion of phenol to PHA is crucial to enhance its efficiency, especially considering phenol's toxicity to microbial cells and the substrate-dependent nature of microbial PHA production. In this review, the mechanisms of phenol biodegradation and PHA biosynthesis are first independently elucidated to comprehend the role of bacteria in these processes. Phenol can be metabolized aerobically via various pathways, including catechol meta-cleavage I and II, catechol ortho-cleavage, protocatechuate ortho-cleavage, and protocatechuate meta-cleavage, as well as anaerobically via 4-hydrozybenzoate and/or n-caproate formation. Meanwhile, PHA can be synthesized through the acetoacetyl-CoA (pathway I), de novo fatty acids synthesis (pathway II), β-oxidation (pathway III), and the tricarboxylic acid (TCA) cycle, with the induction of these pathways are highly dependent on the substrate. Given that the link between these two mechanisms was not comprehensively reported before, the second part of the review delve into understanding phenol conversion into PHA, specifically polyhydroxybutyrate (PHB). While phenol toxicity can inhibit bacterial performance, it can be alleviated through the utilization of microbial mixed culture (MMC), which offers a wider range of metabolic capabilities. Utilizing phenol as a carbon feedstock for PHB accumulation could offer a viable approach to boost PHA's commercialization while addressing the issue of phenol pollution.

PMID:39958774 | PMC:PMC11830346 | DOI:10.1016/j.crmicr.2025.100352

Expert Rev Proteomics. 2025 Feb 16. doi: 10.1080/14789450.2025.2468300. Online ahead of print.

ABSTRACT

INTRODUCTION: Rare diseases (RDs) are a heterogeneous group of diseases recognized as a relevant global health priority but posing aspects of complexity such as: geographical scattering of affected individuals, improper/late diagnosis, limited awareness, difficult surveillance and monitoring, limited understanding of natural history, and lack of treatment. Usually, RDs have a pediatric onset and are life-long, multisystemic, and associated with a poor prognosis.

AREAS COVERED: In this work, we review how high-throughput omics technologies such as genomics, transcriptomics, proteomics, metabolomics, epigenomics, and other well-established omics, which are increasingly more affordable and efficient, can be applied to the study of RDs promoting diagnosis, understanding of pathological mechanisms, biomarker discovery and identification of treatments.

EXPERT OPINION: RDs, despite their challenges, offer a niche where collaborative efforts and personalized treatment strategies might be feasible using omics technologies. Specialized consortia fostering multidisciplinary collaboration, data sharing, and the development of biobanks and registries can be built; multi-omics approaches, including so far less exploited omics technologies, along with the implementation of AI tools can be undertaken to deepen our understanding of RDs, driving biomarker discovery and clinical interventions. Nevertheless, technical, ethical, legal and societal issues must be clearly defined and addressed.

PMID:39956998 | DOI:10.1080/14789450.2025.2468300

J Math Biol. 2025 Feb 16;90(3):31. doi: 10.1007/s00285-025-02191-3.

ABSTRACT

In this paper we introduce a formalism that allows to describe the response of a part of a biochemical system in terms of renewal equations. In particular, we examine under which conditions the interactions between the different parts of a chemical system, described by means of linear ODEs, can be represented in terms of renewal equations. We show also how to apply the formalism developed in this paper to some particular types of linear and non-linear ODEs, modelling some biochemical systems of interest in biology (for instance, some time-dependent versions of the classical Hopfield model of kinetic proofreading). We also analyse some of the properties of the renewal equations that we are interested in, as the long-time behaviour of their solution. Furthermore, we prove that the kernels characterising the renewal equations derived by biochemical system with reactions that satisfy the detail balance condition belong to the class of completely monotone functions.

PMID:39956846 | DOI:10.1007/s00285-025-02191-3

J Allergy Clin Immunol. 2025 Feb 14:S0091-6749(25)00170-8. doi: 10.1016/j.jaci.2025.01.044. Online ahead of print.

NO ABSTRACT

PMID:39956282 | DOI:10.1016/j.jaci.2025.01.044

Asian Pac J Allergy Immunol. 2025 Feb 16. doi: 10.12932/AP-131223-1749. Online ahead of print.

ABSTRACT

BACKGROUND: Atopic dermatitis (AD) and food allergy (FA) often originate early in life. Gut microbiota interactions with the host immune system influence allergy development, yet the distinct gut microbiome and functional profiles in individuals with AD, FA, or both AD+FA remain underexplored.

OBJECTIVE: We investigated microbial colonization and proteomic profiles in infants with AD, FA, and AD+FA compared to age- and sex-matched controls from the Allergy Development in Early Life and Associated Factors in the Thai Birth Cohort (ALICE).

METHODS: Gut microbiomes from stool samples were analyzed using 16S sequencing, and proteomic analysis was conducted by liquid chromatography-tandem mass spectrometry.

RESULTS: The study included 16 AD, 5 FA, 5 AD+FA subjects, and 26 controls. AD+FA group exhibited the most severe dysbiosis. Enrichment of proteins involved in methionine biosynthesis in Bifidobacterium scardovii and high Erysipelotrichaceae colonization suggest a link to high-fat diets, known to reduce intestinal short-chain fatty acid and serotonin levels, contributing to allergies. Erysipelotrichaceae in AD+FA groups also expressed proteins related to histidine degradation. Low Bifidobacteriaceae levels were noted in FA and AD+FA, with more pathogenic strains colonized. Increased Bacteroidaceae in FA and AD+FA and Enterobacteriaceae in FA were detected. Pathways involving vitamin B1, a ligand for proliferator-activated receptor-γ (PPAR-γ) from Enterobacteriaceae could promote TH2 cells, type 2 innate lymphoid cells, and M2 macrophages, likely contribute to allergic inflammation.

CONCLUSIONS: AD+FA phenotype exhibited the most distinctive gut microbiome alterations, highlighting unique dysbiosis patterns. Microbiome biosynthesis pathways involving metabolism of methionine, histidine, serotonin, and vitamin B1 point to new targets for modifying or treating AD and FA.

PMID:39955638 | DOI:10.12932/AP-131223-1749

Environ Microbiome. 2025 Feb 15;20(1):23. doi: 10.1186/s40793-025-00683-9.

ABSTRACT

BACKGROUND: The variation in fungal community composition within a single habitat space has been extensively studied in forest ecosystems. However, the spatial and temporal distribution of fungi across contiguous habitats, particularly at a local scale and in tropical regions, remains underexplored. In this study, we examined the fungal community composition across multiple habitats proximal to each other over two seasons in seven Fagaceae species in Taiwanese broadleaf forests. We tested how local spatial scale and habitat influence community assembly.

RESULTS: Using a metabarcoding approach, we sequenced ITS2 regions from 864 samples collected from four distinct habitats-leaves, twigs, litter, and soil. We identified 11,600 fungal amplicon sequence variants (ASVs), with community composition differing significantly between habitats proximal to each other. Generalized dissimilarity modeling (GDM) revealed that spatial distance, interacting with precipitation, was the strongest predictor of fungal turnover, particularly in the phyllosphere. Normalized Stochasticity Ratio (NST) analyses further highlighted contrasting assembly processes, with deterministic influences dominating in the phyllosphere habitat, while stochasticity prevailed in soil and litter. Random forest analysis accurately classified habitats based on ASVs' relative abundances, with strong predictors were mostly habitat-specific ASVs prevalent in soil. Misclassified samples were due to secondary contact of fungi between adjacent habitats. Co-occurrence network analysis revealed more complex and deterministic networks in leaf and twig habitats, while soil was driven by stochastic processes and contained most habitat-specific ASVs. A Cladosporium sp. emerged as a keystone species, maintaining network stability across forests.

CONCLUSION: This study reveals how local spatial variation and habitat shape distinct fungal communities in tropical forests, with deterministic processes dominating in some habitats and stochasticity playing a key role in others. We show extremely high turnover in fungal community are present over very short distances and that local fungal taxa are strong habitat predictors. These findings highlight the importance of studying coexisting habitats to gain a deeper understanding of fungal biogeography and ecosystem function.

PMID:39955594 | DOI:10.1186/s40793-025-00683-9

Sci Rep. 2025 Feb 15;15(1):5594. doi: 10.1038/s41598-025-90261-3.

ABSTRACT

Fine particulate matter 2.5 (PM2.5) is a prevalent atmospheric pollutant that is closely associated with asthma. Elderly patients have a high incidence of asthma with a long course of illness. Our previous studies revealed that exposure to PM2.5 diminishes lung function and exacerbates lung damage in elderly rats. In the present study, we investigated whether PM2.5 exposure influences susceptibility to allergic asthma in elderly rats. Brown-Norway elderly rats were treated with ovalbumin (OVA) for different durations before and after PM2.5 exposure. The results from pulmonary function tests and histopathology indicated that early exposure to allergens prior to PM2.5 exposure increased susceptibility to airway hyperresponsiveness and led to severe lung injury in elderly asthmatic rats. Cytokine microarray analysis demonstrated that the majority of cytokines and chemokines were upregulated in OVA-treated rats before and after PM2.5 exposure. Cytological examination showed no change in eosinophil (EOS) counts, yet the amounts of neutrophils (NEU), white blood cells (WBC), lymphocytes (LYM), and monocytes (MON) in the lung lavage fluid of OVA-treated rats were significantly higher than those in control rats before and after PM2.5 exposure, suggesting that PM2.5 affects noneosinophilic asthma in elderly rats. ELISA results from the plasma and lung lavage fluid revealed that the levels of IgG1, IgE, IgG2a and IgG2b were significantly elevated in OVA-treated rats, whereas the level of IgG2b in the lung lavage fluid was significantly lower in rats treated with OVA prior to PM2.5 exposure compared to those treated afterward. A non-targeted metabolomic analysis of plasma identified 202 metabolites, among which 31 metabolites were differentially abundant. Ten metabolites and 11 metabolic pathways were uniquely detected in OVA-treated rats before PM2.5 exposure. Specifically, there were positive or negative correlations between the levels of Th2-associated cytokines (IL-4, IL-5, and IL-13) and six metabolites in the OVA-treated group before PM2.5 exposure, whereas the levels of IL-4 and IL-5 were negatively correlated with five metabolites in the OVA-treated group after PM2.5 exposure. Our findings suggest that PM2.5 exposure could influence the susceptibility of allergic asthma in response to allergens in elderly rats, potentially through changes in plasma metabolites.

PMID:39955443 | DOI:10.1038/s41598-025-90261-3

Sci Rep. 2025 Feb 15;15(1):5643. doi: 10.1038/s41598-025-89667-w.

ABSTRACT

Monoclonal antibodies (mAbs) are considered one of the most game-changing products of the biopharmaceutical industry. The introduction of several diverse and complex formats consisting of several polypeptide chains and engineered with multiple antigen-binding domains has made the manufacturability process particularly challenging, especially in the context of assessing expression levels and yields of the formats. Here we present the largest and most diversified CHO transcriptomics analysis consisting of data derived from 892 different monoclonal cell lines, producing 11 different mAbs with various non-standard, highly complex formats. We apply three robust feature selection methods, one traditional differential expression analysis and two machine learning approaches to identify genes correlated to high product titer and quality. Cnpy3 gene is identified as a novel gene biomarker, showing a very strong negative correlation (Pearson r2 = 0.94) to the overall format productivity. These results were validated by a hold-out data set from cell lines expressing two different antibody formats. Additionally, the expression of Cnpy3 gene is positively correlated to the structural complexity of the examined mAbs. As complexity increases, cellular stress escalates leading to reduced productivity, implicating Cnpy3 as a strong CHO cell lines stress indicator. Thus, we conclude that Cnpy3 gene has the potential to be used as a screening biomarker for assessing format manufacturability and selecting formats and pools with a high potential to deliver subsequent higher productivity rates, resulting in a substantially smarter cell line and process development.

PMID:39955392 | DOI:10.1038/s41598-025-89667-w

Nat Commun. 2025 Feb 15;16(1):1671. doi: 10.1038/s41467-025-56760-7.

ABSTRACT

Cryogenic electron microscopy (cryo-EM), X-ray crystallography, and nuclear magnetic resonance (NMR) contribute structural data that are interchangeable, cross-verifiable, and visualizable on common platforms, making them powerful tools for our understanding of protein structures. Unfortunately, atomic force microscopy (AFM) has so far failed to interface with these structural biology methods, despite the recent development of localization AFM (LAFM) that allows extracting high-resolution structural information from AFM data. Here, we build on LAFM and develop a pipeline that transforms AFM data into 3D-density files (.afm) that are readable by programs commonly used to visualize, analyze, and interpret structural data. We show that 3D-LAFM densities can serve as force fields to steer molecular dynamics flexible fitting (MDFF) to obtain structural models of previously unresolved states based on AFM observations in close-to-native environment. Besides, the .afm format enables direct 3D or 2D visualization and analysis of conventional AFM images. We anticipate that the file format will find wide usage and embed AFM in the repertoire of methods routinely used by the structural biology community, allowing AFM researchers to deposit data in repositories in a format that allows comparison and cross-verification with data from other techniques.

PMID:39955301 | DOI:10.1038/s41467-025-56760-7

Trends Biotechnol. 2025 Feb 14:S0167-7799(25)00006-X. doi: 10.1016/j.tibtech.2025.01.006. Online ahead of print.

ABSTRACT

Valorization of lignocellulosic biomass for sustainable production of high-value chemicals is challenged by the complexity of lignin, a phenolic biopolymer. Beyond the classical lignin monomers derived from p-coumaryl, coniferyl, and sinapyl alcohol, grass lignins incorporate substantial amounts of monolignol p-coumarates that are produced by p-COUMAROYL-CoA:MONOLIGNOL TRANSFERASE (PMT). Here, the CRISPR/Cas9-mediated mutation of ZmPMT1 in maize enabled the design of biomass depleted in p-coumaroylated lignin and enriched in guaiacyl lignin. Lignin-first biorefining of stem biomass from zmpmt1 mutants by reductive catalytic fractionation (RCF) generated a lignin oil depleted in carboxylates and enriched in guaiacyl-derived alcohols, which are desirable substrates for bio-based polyurethane synthesis. The reported lignin engineering in maize is a promising strategy for designing a dual-purpose crop, providing both food and feed, along with a renewable feedstock for the production of plant-based chemicals.

PMID:39955231 | DOI:10.1016/j.tibtech.2025.01.006

Metab Eng. 2025 Feb 13:S1096-7176(25)00012-6. doi: 10.1016/j.ymben.2025.02.003. Online ahead of print.

ABSTRACT

Driven by the urgent need to reduce the reliance on fossil fuels and mitigate environmental impacts, microbial cell factories capable of producing value-added products from renewable resources have gained significant attention over the past few decades. Notably, non-model yeasts with unique physiological characteristics have emerged as promising candidates for industrial applications, particularly for the production of organic acids. Among them, Issatchenkia orientalis stands out for its exceptional natural tolerance to low pH and high osmotic pressure, traits that are critical for overcoming the limitations of conventional microbial organisms. The acid tolerance of I. orientalis enables organic acid production under low pH conditions, bypassing the need for expensive neutral pH control typically required in conventional processes. Organic acids produced by I. orientalis, such as lactic acid, succinic acid, and itaconic acid, are widely used as building blocks for bioplastics, food additives, and pharmaceuticals. This review summarizes the key findings from systems biology studies on I. orientalis over the past two decades, providing insights into its unique metabolic and physiological traits. Advances in genetic tool development for this non-model yeast are also discussed, enabling targeted metabolic engineering to enhance its production capabilities. Additionally, case studies are highlighted to illustrate the potential of I. orientalis as a platform organism. Finally, the remaining challenges and future directions are addressed to further develop I. orientalis into a robust and versatile microbial cell factory for sustainable biomanufacturing.

PMID:39954846 | DOI:10.1016/j.ymben.2025.02.003

J Allergy Clin Immunol Pract. 2025 Feb 13:S2213-2198(25)00164-3. doi: 10.1016/j.jaip.2025.01.039. Online ahead of print.

ABSTRACT

BACKGROUND: α1-antitrypsin deficiency is caused by rare pathogenic variants in SERPINA1, the strongest genetic risk factor for COPD. Few studies have evaluated the effects of SERPINA1 variation on asthma severity accounting for critical gene-by-environment interactions with smoking.

OBJECTIVE: To characterize the influence of SERPINA1 variation on asthma severity.

METHODS: DNA samples from 847 non-Hispanic whites and 446 African Americans from the Severe Asthma Research Program underwent SERPINA1 resequencing to identify rare variants. An independent population of 1,955 individuals with asthma and α1-antitrypsin concentrations from a Cleveland Clinic Health System (CCHS) database were evaluated for severity measures.

MEASUREMENTS AND MAIN RESULTS: In whites, a history of minimum smoking significantly interacted with SERPINA1 low-to-rare frequency variation to determine risk for asthma-related healthcare utilization. This was attributed to PI type Z heterozygotes (MZ, N=11) who had a higher frequency of ED visits (6 [54.5%] MZ heterozygotes, OR=7.60, 95%CI=1.71-39.7, p=0.010), hospitalization (5 [45.5%], OR=16.1, 95%CI=2.64-150.4, p=0.0050) in the past year, and lifetime ICU admissions (6 [54.5%], OR=12.5, 95%CI=2.44-75.6, p=0.0032) compared to 146 individuals without SERPINA1 variants (30 [20.5%] reporting ED visits, 17 [11.6%] hospitalization, 15 [10.3%] ICU admission). SERPINA1 variant-ever smoking interactions in African Americans for ED visits (p=0.069) related to four of six compound heterozygotes reporting an ED visit. In CCHS, α1-antitrypsin concentrations were inversely associated with moderate-to-severe asthma risk (OR=0.97 per 10 mg/dL increase in α1-antitrypsin, 95%CI=0.94-0.99, p=0.010) and exacerbations (OR=0.84 per 10 mg/dL, 95%CI=0.76-0.94, p=0.002).

CONCLUSIONS: SERPINA1 variation and α1-antitrypsin concentrations impact asthma severity through gene-environment interactions with minimum smoking.

PMID:39954727 | DOI:10.1016/j.jaip.2025.01.039

Cell Stem Cell. 2025 Feb 12:S1934-5909(25)00010-4. doi: 10.1016/j.stem.2025.01.010. Online ahead of print.

ABSTRACT

Acute myeloid leukemia (AML) is an aggressive hematopoietic malignancy characterized by the blockage of myeloid cell differentiation and uncontrolled proliferation of immature myeloid cells. Here, we show that paraspeckle component 1 (PSPC1) is aberrantly overexpressed and associated with poor survival in AML patients. Using human AML cells and mouse models, we demonstrate that PSPC1 is not required for normal hematopoiesis, but it is critical and essential for AML cells to maintain their leukemic characteristics. PSPC1 loss induces robust differentiation, suppresses proliferation, and abolishes leukemogenesis in diverse AML cells. Mechanistically, PSPC1 exerts a pro-leukemia effect by regulating a unique leukemic transcription program via cooperative chromatin binding with PU.1 and activation of tumor-promoting genes, including NDC1, which is not previously implicated in AML. Our findings uncover a unique and crucial role of PSPC1 dependency in AML and highlight its potential as a promising therapeutic target for AML.

PMID:39954676 | DOI:10.1016/j.stem.2025.01.010

Cell Rep Methods. 2025 Feb 10:100984. doi: 10.1016/j.crmeth.2025.100984. Online ahead of print.

ABSTRACT

Probabilistic graphical models are powerful tools to quantify, visualize, and interpret network dependencies in complex biological systems such as high-throughput -omics. However, many graphical models assume sample homogeneity, limiting their effectiveness. We propose a flexible Bayesian approach called graphical regression (GraphR), which (1) incorporates sample heterogeneity at different scales through a regression-based formulation, (2) enables sparse sample-specific network estimation, (3) identifies and quantifies potential effects of heterogeneity on network structures, and (4) achieves computational efficiency via variational Bayes algorithms. We illustrate the comparative efficiency of GraphR against existing state-of-the-art methods in terms of network structure recovery and computational cost across multiple settings. We use GraphR to analyze three multi-omic and spatial transcriptomic datasets to investigate inter- and intra-sample molecular networks and delineate biological discoveries that otherwise cannot be revealed by existing approaches. We have developed a GraphR R package along with an accompanying Shiny App that provides comprehensive analysis and dynamic visualization functions.

PMID:39954675 | DOI:10.1016/j.crmeth.2025.100984

Cell Rep Methods. 2025 Feb 10:100985. doi: 10.1016/j.crmeth.2025.100985. Online ahead of print.

ABSTRACT

Cell-cell interaction (CCI) networks are key to understanding disease progression and treatment response. However, existing methods for inferring these networks often aggregate data across patients or focus on cell-type level interactions, providing a generalized overview but overlooking patient heterogeneity and local network structures. To address this, we introduce "random cell-cell interaction generator" (RaCInG), a model based on random graphs to derive personalized networks leveraging prior knowledge on ligand-receptor interactions and bulk RNA sequencing data. We applied RaCInG to 8,683 cancer patients to extract 643 network features related to the tumor microenvironment and unveiled associations with immune response and subtypes, enabling prediction and explanation of immunotherapy responses. RaCInG demonstrated robustness and showed consistencies with state-of-the-art methods. Our findings highlight RaCInG's potential to elucidate patient-specific network dynamics, offering insights into cancer biology and treatment responses. RaCInG is poised to advance our understanding of complex CCI s in cancer and other biomedical domains.

PMID:39954673 | DOI:10.1016/j.crmeth.2025.100985

Cell Rep Methods. 2025 Feb 10:100990. doi: 10.1016/j.crmeth.2025.100990. Online ahead of print.

ABSTRACT

The need for a deeper understanding of adverse drug reaction (ADR) mechanisms is vital for improving drug safety and repurposing. This study introduces Drug Adverse Reaction Mechanism Explainer (DREAMER), a network-based framework that uses a comprehensive knowledge graph to uncover molecular mechanisms underlying ADRs and disease phenotypes. By examining shared phenotypes of drugs and diseases and their effects on protein-protein interaction networks, DREAMER identifies proteins linked to ADR mechanisms. Applied to 649 ADRs, DREAMER identified molecular mechanisms for 67 ADRs, including ventricular arrhythmia and metabolic acidosis, and emphasized pathways like GABAergic signaling and coagulation proteins in personality disorders and intracranial hemorrhage. We further demonstrate the application of DREAMER in drug repurposing and propose sotalol, ranolazine, and diltiazem as candidate drugs to be repurposed for cardiac arrest. In summary, DREAMER effectively detects molecular mechanisms underlying phenotypes, emphasizing the importance of network-based analyses with integrative data for enhancing drug safety and accelerating the discovery of novel therapeutic strategies.

PMID:39954672 | DOI:10.1016/j.crmeth.2025.100990

Biosens Bioelectron. 2025 Feb 6;276:117228. doi: 10.1016/j.bios.2025.117228. Online ahead of print.

ABSTRACT

Hepatocellular carcinoma (HCC) poses a significant global health burden, with escalating incidence rates and substantial mortality. The predominant etiological factors include liver cirrhosis (LC) and chronic hepatitis B infections (CHB). Surveillance primarily relies on ultrasound and Alpha-fetoprotein (AFP), yet their efficacy, particularly in early HCC detection, is limited. Hence, there is a critical need for accurate non-invasive biomarkers to enhance surveillance and early diagnosis. Extracellular vesicles (EVs) hold promises as stable carriers of signaling molecules, offering potential in tumor diagnosis. Our study developed a novel tidal microfluidic chip for label-free EV isolation, enabling rapid and efficient enrichment from small plasma volumes. Through transcriptome sequencing and single-cell analysis, we identified HMMR and B4GALT2 as promising HCC-associated biomarkers in EVs. In a comprehensive clinical evaluation, bi-mRNAs in EVs exhibited superior diagnostic performance over AFP, particularly in distinguishing early-stage HCC or AFP-negative cases from high-risk individuals (CHB/LC). Notably, our study demonstrated the potential of bi-mRNAs to complement imaging examinations, enabling early detection of HCC lesions. In conclusion, the tidal microfluidic chip offers a practical solution for EV isolation, with the integration of EV-based biomarkers presenting opportunities for improved early detection and management of HCC in clinical practice.

PMID:39954520 | DOI:10.1016/j.bios.2025.117228

Europace. 2025 Feb 15:euaf034. doi: 10.1093/europace/euaf034. Online ahead of print.

NO ABSTRACT

PMID:39953950 | DOI:10.1093/europace/euaf034

New Phytol. 2025 Feb 15. doi: 10.1111/nph.70009. Online ahead of print.

ABSTRACT

Stomata regulate plant gas exchange via repeated turgor-driven changes of guard cell shape, thereby adjusting pore apertures. Grasses, which are among the most widespread plant families on the planet, are distinguished by their unique stomatal structure, which is proposed to have significantly contributed to their evolutionary and agricultural success. One component of their structure, which has received little attention, is the presence of a discontinuous adjoining cell wall of the guard cell pair. Here, we demonstrate the presence of these symplastic connections in a range of grasses and use finite element method simulations to assess hypotheses for their functional significance. Our results show that opening of the stomatal pore is maximal when the turgor pressure in dumbbell-shaped grass guard cells is equal, especially under the low pressure conditions that occur during the early phase of stomatal opening. By contrast, we demonstrate that turgor pressure differences have less effect on the opening of kidney-shaped guard cells, characteristic of the majority of land plants, where guard cell connections are rarely or not observed. Our data describe a functional mechanism based on cellular mechanics, which plausibly facilitated a major transition in plant evolution and crop development.

PMID:39953834 | DOI:10.1111/nph.70009