Am J Cardiol. 2025 Jan 25:S0002-9149(25)00039-6. doi: 10.1016/j.amjcard.2025.01.015. Online ahead of print.

ABSTRACT

Advances in personalized medicine and Systems Biology have introduced probabilistic models and error discovery to cardiovascular care, aiding disease prevention and procedural planning. However, clinical application faces cultural, technical, and methodological hurdles. Patient autonomy remains essential, with shared decision-making (SDM) gaining importance in managing complex cardiovascular treatment options. Effective SDM relies on collaboration between providers and patients, guided by P5 Medicine principles, which combine psycho-cognitive considerations with predictive, personalized, preventive, and participatory care. Here we propose a three-step methodological proposal for implementing SDM and enhancing consent acquisition in cardiovascular care. The approach emphasizes personalized patient engagement and the need for clear, comprehensive consent processes. It identifies and addresses significant gaps in current practices, including the complexity of consent language, information dispersion, and the specific needs of vulnerable populations. Issues of Medical Responsibility and/or Liability may raise in the case of absence of consent acquisition or invalid consent due to insufficient/incorrect information. The International Guidelines on Medico-Legal Methods of Ascertainment and Evaluation Criteria are reported. In conclusion, the paper proposes practical solutions, including the use of artificial intelligence (AI) to enhance decision-making and patient counseling, and strategies to ensure that consent processes are both thorough and legally sound and respectful to the individual's autonomy.

PMID:39870321 | DOI:10.1016/j.amjcard.2025.01.015

Brain Behav Immun. 2025 Jan 25:S0889-1591(25)00025-X. doi: 10.1016/j.bbi.2025.01.016. Online ahead of print.

ABSTRACT

This study investigated the neural correlates of perceiving visual contagion cues characteristic of respiratory infections through functional magnetic resonance imaging (fMRI). Sixty-two participants (32f/ 30 m; ∼25 years on average) watched short videos depicting either contagious or non-contagious everyday situations, while their brain activation was continuously measured. We further measured the release of secretory immunoglobulin A (sIgA) in saliva to examine the first-line defensive response of the mucosal immune system. Perceiving sneezing and sick individuals compared to non-contagious individuals triggered increased activation in the anterior insula and other regions of the neuroimmune axis, that have been implicated in the somatosensory representation of the respiratory tract, and further led to increased release of sIgA. In line with predictions, this contagion cue-related activation of the insula was positively correlated with both perceived contagiousness and disgust evoked by the videos, as well as with the mucosal sIgA response. In contrast, the amygdala exhibited heightened activation to all videos featuring humans, regardless of explicit signs of contagion, indicating a nonspecific alertness to human presence. Nevertheless, amygdala activation was also correlated with the disgust ratings of each video. Collectively, these findings outline a neuroimmune mechanism for the processing of respiratory contagion cues. While the insula coordinates central and peripheral immune activation to match the perceived contagion threat, supposedly by triggering both increased sIgA release and contagion-related cognitions, the amygdala may rather act as an alerting system for social situations with a heightened transmission risk. This proactive neuroimmune response may help humans to manage contagion risks, that are difficult to avoid, by activating physiological and cognitive countermeasures in reaction to typical symptoms of respiratory infection, which prepares the organism for subsequent pathogen exposure.

PMID:39870198 | DOI:10.1016/j.bbi.2025.01.016

PLoS Genet. 2025 Jan 27;21(1):e1011577. doi: 10.1371/journal.pgen.1011577. Online ahead of print.

ABSTRACT

Some animals can regenerate large missing regions of their nervous system, requiring mechanisms to restore the pattern, numbers, and wiring of diverse neuron classes. Because injuries are unpredictable, regeneration must be accomplished from an unlimited number of starting points. Coordinated regeneration of neuron-glia architecture is thus a major challenge and remains poorly understood. In planarians, neurons and glia are regenerated from distinct progenitors. We found that planarians first regenerate neurons expressing a Delta-encoding gene, delta-2, at key positions in the central and peripheral nervous systems. Planarian glia are specified later from dispersed Notch-1-expressing mesoderm-like phagocytic progenitors. Inhibition of delta-2 or notch-1 severely reduced glia in planarians, but did not affect the specification of other phagocytic cell types. Loss of several delta-2-expressing neuron classes prevented differentiation of the glia associated with them, whereas transplantation of delta-2-expressing photoreceptor neurons was sufficient for glia formation at an ectopic location. Our results suggest a model in which patterned delta-2-expressing neurons instruct phagocytic progenitors to locally differentiate into glia, presenting a mechanism for coordinated regeneration of numbers and pattern of cell types.

PMID:39869602 | DOI:10.1371/journal.pgen.1011577

Int J Syst Evol Microbiol. 2025 Jan;75(1). doi: 10.1099/ijsem.0.006648.

ABSTRACT

An obligately anaerobic, spore-forming sulphate-reducing bacterium, strain SB140T, was isolated from a long-term continuous enrichment culture that was inoculated with peat soil from an acidic fen. Cells were immotile, slightly curved rods that stained Gram-negative. The optimum temperature for growth was 28 °C. Strain SB140T grew at pH 4.0-7.5 with an optimum pH of 6.0-7.0 using various electron donors and electron acceptors. Yeast extract, sugars, alcohols and organic acids were used as electron donors for sulphate reduction. SB140T additionally used elemental sulphur and nitrate as electron acceptors but not sulphite, thiosulphate or iron(III) provided as ferrihydrite and fumarate. The 16S rRNA gene sequence placed strain SB140T in the genus Desulfosporosinus of the phylum Bacillota. The predominant cellular fatty acids were iso-C15 : 0 (52.6%) and 5,7 C15 : 2 (19.9%). The draft genome of SB140T (5.42 Mbp in size) shared 77.4% average nucleotide identity with the closest cultured relatives Desulfosporosinus acididurans M1T and Desulfosporosinus acidiphilus SJ4T. On the basis of phenotypic, phylogenetic and genomic characteristics, SB140T was identified as a novel species within the genus Desulfosporosinus, for which we propose the name Desulfosporosinus paludis sp. nov. The type strain is SB140T (=DSM 117342T=JCM 39521T).

PMID:39869511 | DOI:10.1099/ijsem.0.006648

J Virol. 2025 Jan 27:e0171724. doi: 10.1128/jvi.01717-24. Online ahead of print.

ABSTRACT

The imperative for developing robust tools to detect, analyze, and characterize viruses has become increasingly evident as they continue to threaten human health. In this review, we focus on recent advancements in studying human viruses with flow virometry (FV), an emerging technique that has gained considerable momentum over the past 5 years. These advancements include the application of FV in viral surface phenotyping, viral protein functionality, virus sorting, vaccine development, and diagnostics. With examples illustrated using primary data from our recent studies, we demonstrate that FV is a powerful yet underutilized methodology that, when employed with best practices and experimental rigor, can be highly valuable for studying individual virion heterogeneity, virus phenotypes, and virus-antibody interactions. In this review, we also address the current challenges when performing FV studies, propose strategies to overcome these obstacles, and outline best practices for both new and experienced researchers. Finally, we discuss the promising future prospects of FV within the broader context of virology research.

PMID:39868829 | DOI:10.1128/jvi.01717-24

Biol Aujourdhui. 2024;218(3-4):91-98. doi: 10.1051/jbio/2024009. Epub 2025 Jan 27.

ABSTRACT

The advent of high-throughput omics data and the generation of new algorithms provide the biologists with the opportunity to explore living processes in the context of systems biology aiming at revealing the gene interactions, the networks underlying complex cellular functions. In this article, we discuss two methods for gene network reconstruction, WGCNA (Weighted Gene Correlation Network Analysis) developed by Steve Horvath and collaborators in 2008, and MIIC (Multivariate Information-based Inductive Causation) developed by Hervé Isambert and his team in 2017 and 2024. These two methods are complementary, WGCNA generating undirected networks in which most gene-to-gene interactions are indirect, while MIIC reveals direct interactions and some causal links. We illustrate these aspects according to our own work aiming at identifying the gene interactions underlying the hematopoietic stem cell supportive activity of mesenchymal stromal cells at an early developmental stage.

PMID:39868708 | DOI:10.1051/jbio/2024009

Plant J. 2025 Jan;121(2):e17220. doi: 10.1111/tpj.17220.

ABSTRACT

The traditional Chinese medicinal plant Prunella vulgaris contains numerous triterpene saponin metabolites, notably ursolic and oleanolic acid saponins, which have significant pharmacological values. Despite their importance, the genes responsible for synthesizing these triterpene saponins in P. vulgaris remain unidentified. This study used a comprehensive screening methodology, combining phylogenetic analysis, gene expression assessment, metabolome-transcriptome correlation and co-expression analysis, to identify candidate genes involved in triterpene saponins biosynthesis. Nine candidate genes - two OSCs, three CYP716s and four UGT73s - were precisely identified from large gene families comprising hundreds of members. These genes were subjected to heterologous expression and functional characterization, with enzymatic activity assays confirming their roles in the biosynthetic pathway, aligning with bioinformatics predictions. Analysis revealed that these genes originated from a whole-genome duplication (WGD) event in P. vulgaris, highlighting the potential importance of WGD for plant metabolism. This study addresses the knowledge gap in the biosynthesis of triterpene saponins in P. vulgaris, establishing a theoretical foundation for industrial production via synthetic biology. Additionally, we present an efficient methodological protocol that integrates evolutionary principles and bioinformatics techniques in metabolite biosynthesis research. This approach holds significant value for studies focused on unraveling various biosynthetic pathways.

PMID:39868644 | DOI:10.1111/tpj.17220

Nucleic Acids Res. 2025 Jan 24;53(3):gkaf028. doi: 10.1093/nar/gkaf028.

ABSTRACT

Genome graphs, including the recently released draft human pangenome graph, can represent the breadth of genetic diversity and thus transcend the limits of traditional linear reference genomes. However, there are no genome-graph-compatible tools for analyzing whole genome bisulfite sequencing (WGBS) data. To close this gap, we introduce methylGrapher, a tool tailored for accurate DNA methylation analysis by mapping WGBS data to a genome graph. Notably, methylGrapher can reconstruct methylation patterns along haplotype paths precisely and efficiently. To demonstrate the utility of methylGrapher, we analyzed the WGBS data derived from five individuals whose genomes were included in the first Human Pangenome draft as well as WGBS data from ENCODE (EN-TEx). Along with standard performance benchmarking, we show that methylGrapher fully recapitulates DNA methylation patterns defined by classic linear genome analysis approaches. Importantly, methylGrapher captures a substantial number of CpG sites that are missed by linear methods, and improves overall genome coverage while reducing alignment reference bias. Thus, methylGrapher is a first step toward unlocking the full potential of Human Pangenome graphs in genomic DNA methylation analysis.

PMID:39868538 | DOI:10.1093/nar/gkaf028

PNAS Nexus. 2025 Jan 16;4(1):pgaf008. doi: 10.1093/pnasnexus/pgaf008. eCollection 2025 Jan.

ABSTRACT

While more data are becoming available on gene activity at different levels of biological organization, our understanding of the underlying biology remains incomplete. Here, we introduce a metabolic efficiency framework that considers highly expressed proteins (HEPs), their length, and biosynthetic costs in terms of the amino acids (AAs) they contain to address the observed balance of expression costs in cells, tissues, and cancer transformation. Notably, the combined set of HEPs in either cells or tissues shows an abundance of large and costly proteins, yet tissues compensate this with short HEPs comprised of economical AAs, indicating a stronger tendency toward mitigating costs. We additionally observe that short proteins are prevalent HEPs across individual cells and tissues, whereas long ones are more specific. Furthermore, the precise proportion of short, long, economical, or costly HEP classes indicates that particular cell types and tissues align more closely with the metabolic efficiency model, with some tissues displaying behavior akin to their constituent cells. Finally, tumors typically increase the production of short and low-cost HEPs compared with matched normal tissues, while genes that decrease their high expression levels in tumors often tend to be associated with high costs. Overall, the metabolic efficiency framework serves as a useful simplifying model for interpreting genome-wide expression data across scales.

PMID:39867669 | PMC:PMC11759310 | DOI:10.1093/pnasnexus/pgaf008

Bioinform Adv. 2025 Jan 21;5(1):vbae209. doi: 10.1093/bioadv/vbae209. eCollection 2025.

ABSTRACT

MOTIVATION: Missing values are prevalent in high-throughput measurements due to various experimental or analytical reasons. Imputation, the process of replacing missing values in a dataset with estimated values, plays an important role in multivariate and machine learning analyses. The three missingness patterns, including missing completely at random, missing at random, and missing not at random, describe unique dependencies between the missing and observed data. The optimal imputation method for each dataset depends on the type of data, the cause of the missingness, and the nature of relationships between the missing and observed data. The challenge is to identify the optimal imputation solution for a given dataset.

RESULTS: ImpLiMet: is a user-friendly web-platform that enables users to impute missing data using eight different methods. For a given dataset, ImpLiMet suggests the optimal imputation solution through a grid search-based investigation of the error rate for imputation across three missingness data simulations. The effect of imputation can be visually assessed by histogram, kurtosis, and skewness, as well as principal component analysis comparing the impact of the chosen imputation method on the distribution and overall behavior of the data.

AVAILABILITY AND IMPLEMENTATION: ImpLiMet is freely available at https://complimet.ca/shiny/implimet/ and https://github.com/complimet/ImpLiMet.

PMID:39867531 | PMC:PMC11761345 | DOI:10.1093/bioadv/vbae209

ACS Cent Sci. 2025 Jan 3;11(1):25-35. doi: 10.1021/acscentsci.4c01437. eCollection 2025 Jan 22.

ABSTRACT

Antimicrobial drug resistance (AMR) is a pressing global human health challenge. Humans face one of their grandest challenges as climate change expands the habitat of vectors that bear human pathogens, incidences of nosocomial infections rise, and new antibiotics discovery lags. AMR is a multifaceted problem that requires a multidisciplinary and an "all-hands-on-deck" approach. As chemical microbiologists, we are well positioned to understand the complexities of AMR while seeing opportunities for tackling the challenge. In this Outlook, we focus on vulnerabilities of human pathogens and posit that they represent "opportunity targets" for which few modulatory ligands exist. We center our attention on proteins in Gram-negative organisms, which are recalcitrant to many antibiotics because of their external membrane barrier. Our hope is to highlight such targets and explore their potential as "druggable" proteins for infectious disease mitigation. We posit that success in this endeavor will introduce new classes of antibiotics that might alleviate some of the current pressing AMR concerns.

PMID:39866699 | PMC:PMC11758222 | DOI:10.1021/acscentsci.4c01437

Heliyon. 2025 Jan 2;11(1):e41633. doi: 10.1016/j.heliyon.2025.e41633. eCollection 2025 Jan 15.

ABSTRACT

Isoxazole and oxadiazole derivatives inhibiting 3-hydroxykynurenine transaminase (3HKT) are potential larvicidal candidates. This study aims to identify more suited potential inhibitors of Anopheles gambiae 3HKT (Ag3HKT) through molecular docking and molecular dynamics simulation. A total of 958 compounds were docked against Anopheles gambiae 3HKT (PDB ID: 2CH2) using Autodock vina and Autodock4. The top three identified hits were subjected to 300 ns molecular dynamics simulation using AMBER 18 and ADMET analysis using SWISSADME predictor and ADMETSAR. Replacement of alkyl attachment on C5 of isoxazole or oxadiazole derivative with a cycloalkyl group yielded compounds with lower binding energy than their straight chain counterparts. The top three compounds were brominated compounds, 2-[3-(4-bromophenyl)-1,2-oxazol-5-yl]cyclopentane-1-carboxylic acid, 2-[3-(4-bromophenyl)-1,2,4-oxadiazol-5-yl]cyclopentane-1-carboxylic acid, 3-[3-(4-bromo-2-methylphenyl)-1,2,4-oxadiazol-5-yl]cyclopentane-1-carboxylic acid, and they had binding energies of -8.58, -8.25, and -8.18 kcal/mol in virtual screening against 2CH2 protein target, respectively. These compounds were predicted to be less toxic than temephos, a standard larvicide and more biodegradable than previously reported inhibitors. The three compounds exhibited a greater stabilizing effect on 2CH2 protein target than 4-[3-(4-bromophenyl)-1,2,4-oxadiazol-5-yl]butanoic acid, a previously reported inhibitor candidate with good larvicidal activity on Aedes aegypti. Further thermodynamic calculations revealed that the top three compounds possessed total binding energies (ΔGbind) of -26.64 kcal/mol, -24.26 kcal/mol and -14.11 kcal/mol, respectively, as compared to -12.02 kcal/mol for 4-[3-(4-bromophenyl)-1,2,4-oxadiazol-5-yl]butanoic acid. These compounds could be better larvicides than previously reported isoxazole or oxadiazole derivatives and safer than temephos.

PMID:39866405 | PMC:PMC11759636 | DOI:10.1016/j.heliyon.2025.e41633

Development. 2025 Jan 27:dev.204397. doi: 10.1242/dev.204397. Online ahead of print.

ABSTRACT

Numerous regulators of cardiomyocyte (CM) proliferation have been identified, yet how they coordinate during cardiac development or regeneration is poorly understood. Here, we developed a computational model of the CM proliferation regulatory network to obtain key regulators and systems-level understanding. The model defines five modules (DNA replication, mitosis, cytokinesis, growth factor, Hippo pathway) and integrates them into a network of 72 nodes and 88 reactions that correctly predicts 73 of 78 (93.6%) independent experiments from the literature. The model predicts that in response to YAP activation, the Hippo module crosstalks to the growth factor module via PI3K and cMyc to drive cell cycle activity. This predicted YAP-cMyc axis is validated experimentally in rat cardiomyocytes and further supported by YAP-stimulated cMyc open chromatin and mRNA in mouse hearts. This validated computational model predicts how individual regulators and modules coordinate to control CM proliferation.

PMID:39866065 | DOI:10.1242/dev.204397

Plant J. 2025 Jan;121(2):e17210. doi: 10.1111/tpj.17210.

ABSTRACT

Bacterial wilt caused by Ralstonia solanacearum is a devastating disease affecting a great many crops including peanut. The pathogen damages plants via secreting type Ш effector proteins (T3Es) into hosts for pathogenicity. Here, we characterized RipAU was among the most toxic effectors as ΔRipAU completely lost its pathogenicity to peanuts. A serine residue of RipAU is the critical site for cell death. The RipAU targeted a subtilisin-like protease (AhSBT1.7) in peanut and both protein moved into nucleus. Heterotic expression of AhSBT1.7 in transgenic tobacco and Arabidopsis thaliana significantly improved the resistance to R. solanacearum. The enhanced resistance was linked with the upregulating ERF1 defense marker genes and decreasing pectin methylesterase (PME) activity like PME2&4 in cell wall pathways. The RipAU played toxic effect by repressing R-gene, defense hormone signaling, and AhSBTs metabolic pathways but increasing PMEs expressions. Furthermore, we discovered AhSBT1.7 interacted with AhPME4 and was colocalized at nucleus. The AhPME speeded plants susceptibility to pathogen via mediated cell wall degradation, which inhibited by AhSBT1.7 but upregulated by RipAU. Collectively, RipAU impaired AhSBT1.7 defense for pathogenicity by using PME-mediated cell wall degradation. This study reveals the mechanism of RipAU pathogenicity and AhSBT1.7 resistance, highlighting peanut immunity to bacterial wilt for future improvement.

PMID:39866050 | DOI:10.1111/tpj.17210

Curr Neuropharmacol. 2025 Jan 24. doi: 10.2174/011570159X323666241029171256. Online ahead of print.

ABSTRACT

Epilepsy is a neurological disorder affecting millions of people worldwide. Antiseizure medications (ASM) remain a critical therapeutic intervention for treating epilepsy, notwithstanding the rapid development of other therapies. There have been substantial advances in epilepsy medications over the past three decades, with over 20 ASMs now available commercially. Here we describe the conventional and unique mechanisms of action of ASMs, focusing on everolimus, cannabidiol, cenobamate, fenfluramine, and ganaxolone, the five most recently marketed ASMs. Major obstacles in the development of ASMs are also addressed, particularly drug-resistant epilepsy as well as psychiatric and behavioral adverse effects of ASMs. Moreover, we delve into the mechanisms and comparative efficacy of ASM polytherapy, with remarks on the benefits and challenges in their application in clinical practice. In addition, the characteristics of the ideal ASM are outlined in this review. The review also discusses the development of new potential ASMs, including modifying existing ASMs to improve efficacy and tolerability. Furthermore, we expound on the modulation of γ- aminobutyric acid type A receptor (GABAAR) as a strategy for the treatment of epilepsy and the identification of a GABAAR agonist, isoguvacine, as a potential ASM.

PMID:39865817 | DOI:10.2174/011570159X323666241029171256

Protein Sci. 2025 Feb;34(2):e70023. doi: 10.1002/pro.70023.

ABSTRACT

Proteins' flexibility is a feature in communicating changes in cell signaling instigated by binding with secondary messengers, such as calcium ions, associated with the coordination of muscle contraction, neurotransmitter release, and gene expression. When binding with the disordered parts of a protein, calcium ions must balance their charge states with the shape of calcium-binding proteins and their versatile pool of partners depending on the circumstances they transmit. Accurately determining the ionic charges of those ions is essential for understanding their role in such processes. However, it is unclear whether the limited experimental data available can be effectively used to train models to accurately predict the charges of calcium-binding protein variants. Here, we developed a chemistry-informed, machine-learning algorithm that implements a game theoretic approach to explain the output of a machine-learning model without the prerequisite of an excessively large database for high-performance prediction of atomic charges. We used the ab initio electronic structure data representing calcium ions and the structures of the disordered segments of calcium-binding peptides with surrounding water molecules to train several explainable models. Network theory was used to extract the topological features of atomic interactions in the structurally complex data dictated by the coordination chemistry of a calcium ion, a potent indicator of its charge state in protein. Our design created a computational tool of CaXML, which provided a framework of explainable machine learning model to annotate ionic charges of calcium ions in calcium-binding proteins in response to the chemical changes in an environment. Our framework will provide new insights into protein design for engineering functionality based on the limited size of scientific data in a genome space.

PMID:39865355 | DOI:10.1002/pro.70023

Life Sci Space Res (Amst). 2025 Feb;44:10-22. doi: 10.1016/j.lssr.2024.11.004. Epub 2024 Nov 22.

ABSTRACT

The space environment presents unique stressors, such as microgravity and space radiation, which can induce molecular and physiological changes in living organisms. To identify key reproducible transcriptomic features and explore potential biological roles in space-flown C. elegans, we integrated transcriptomic data from C. elegans subjected to four spaceflights aboard the International Space Station (ISS) and identified 32 reproducibly differentially expressed genes (DEGs). These DEGs were enriched in pathways related to the structural constituent of cuticle, defense response, unfolded protein response, longevity regulation, extracellular structural organization, and signal receptor regulation. Among these 32 DEGs, 13 genes were consistently downregulated across four spaceflight conditions, primarily associated with the structural constituent of the cuticle. The remaining genes, involved in defense response, unfolded protein response, and longevity regulation pathway, exhibited distinct patterns depending on spaceflight duration: they were downregulated during short-term spaceflights but upregulated during long-term spaceflights. To explore the potential space stressors responsible for these transcriptomic changes, we performed qRT-PCR experiments on C. elegans exposed to simulated microgravity and low-dose radiation. Our results demonstrated that cuticle-related gene expression was significantly downregulated under both simulated microgravity and low-dose radiation conditions. In contrast, almost all genes involved in defense response, unfolded protein response, and longevity regulation pathway were downregulated under simulated microgravity but upregulated under low-dose radiation exposure. These findings suggest that both microgravity and space radiation inhibit cuticle formation; microgravity as the primary stressor inhibit defense response, unfolded protein response, and longevity regulation pathway during short-term spaceflights, while space radiation may promote these processes during long-term spaceflights. In summary, through integrated spaceflight transcriptomic analyses and simulated space experiments, we identified key transcriptomic features and potential biological functions in space-flown C. elegans, shedding light on the space stressors responsible for these changes. This study provides new insights into the molecular and physiological adaptations of C. elegans to spaceflight, highlighting the distinct impacts of microgravity and space radiation.

PMID:39864902 | DOI:10.1016/j.lssr.2024.11.004

Environ Toxicol Chem. 2025 Jan 6:vgae063. doi: 10.1093/etojnl/vgae063. Online ahead of print.

ABSTRACT

An adverse outcome pathway (AOP) framework maps the sequence of events leading to adverse outcomes from chemical exposures, providing a mechanistic understanding often absent in traditional methods. The quantitative AOP (qAOP) advances AOP by integrating quantitative data and mathematical modeling, thereby providing a more precise comprehension of relationships between molecular initiating events, key events, and adverse outcomes. This review critically examines three primary methodologies: systems toxicology, regression modeling, and Bayesian network modeling, highlighting their strengths, limitations, and specific data requirements within toxicology. Through an analysis of current methodologies and challenges, this review emphasizes the integration of experimental and computational approaches to elucidate key event relationships and proposes strategies for overcoming limitations through standardized protocols and advanced computational tools. By outlining future research directions and the potential of qAOPs to transform chemical risk assessment, this review aims to contribute to the advancement of regulatory science and the protection of public health and the environment.

PMID:39864436 | DOI:10.1093/etojnl/vgae063

Cell Rep. 2025 Jan 25;44(2):115241. doi: 10.1016/j.celrep.2025.115241. Online ahead of print.

ABSTRACT

Hematopoietic stem cells (HSCs) possess the capacity to regenerate the entire hematopoietic system. However, the precise HSC dynamics in the early post-transplantation phase remain an enigma. Clinically, the initial hematopoiesis in the post-transplantation period is critical, necessitating strategies to accelerate hematopoietic recovery. Here, we uncovered the spatiotemporal dynamics of early active hematopoiesis, "hematopoietic cell inflation," using a highly sensitive in vivo imaging system. Hematopoietic cell inflation occurs in three peaks in the spleen after transplantation, with common myeloid progenitors (CMPs), notably characterized by HSC-like signatures, playing a central role. Leveraging these findings, we developed expanded CMPs (exCMPs), which exhibit a gene expression pattern that selectively proliferates in the spleen and promotes hematopoietic expansion. Moreover, universal exCMPs supported early hematopoiesis in allogeneic transplantation. Human universal exCMPs have the potential to be a viable therapeutic enhancement for all HSC transplant patients.

PMID:39864058 | DOI:10.1016/j.celrep.2025.115241

J Immunother Cancer. 2025 Jan 25;13(1):e010083. doi: 10.1136/jitc-2024-010083.

ABSTRACT

BACKGROUND: B7 homolog 3 (B7-H3), an overexpressed antigen across multiple solid cancers, represents a promising target for CAR T cell therapy. This study investigated the expression of B7-H3 across various solid tumors and developed novel monoclonal antibodies (mAbs) targeting B7-H3 for CAR T cell therapy.

METHODS: Expression of B7-H3 across various solid tumors was evaluated using RNA-seq data from TCGA, TARGET, and GTEx datasets and by flow cytometry staining. B7-H3-specific mAbs were developed by immunizing mice with human B7-H3, screening with ELISA, and analyzing kinetics with surface plasmon resonance. These mAbs were used to create second-generation CAR constructs, which were evaluated in vitro and in vivo for their antitumor function.

RESULTS: We identified four mAb clones from immunized mice, with three demonstrating high specificity and affinity. The second-generation B7-H3 CAR T cells derived from these mAbs exhibited robust cytotoxicity against B7-H3-positive targets and successfully infiltrated and eliminated tumor spheroids in vitro. In a xenograft mouse model of glioblastoma, these CAR T cells, particularly those derived from clone A2H4, eradicated the primary tumor, and effectively controlled rechallenge tumor, resulting in prolonged survival of the xenograft mice. In vivo T cell trafficking revealed high accumulation and persistence of A2H4-derived CAR T cells at the tumor site.

CONCLUSIONS: Our results provide novel B7-H3-targeted CAR T cells with high efficacy, paving the way for clinical translation of solid tumor treatment.

PMID:39863300 | DOI:10.1136/jitc-2024-010083