Theor Biol Forum. 2024 Jul 1;117(1-2):25-32. doi: 10.19272/202411402003.

ABSTRACT

Inheritance is a fundamental process that shapes the diversity of life on Earth. While DNA is commonly considered the primary carrier of genetic information, recent advances in molecular biology have shown that other forms of information, such as epigenetic modifications and non-coding RNAs, play important roles in inheritance. Here, we propose a theoretical framework that unifies the diverse sources of inheritance under the common concept of information. we argue that information, in its broadest sense, is the basis of inheritance.

PMID:40151859 | DOI:10.19272/202411402003

J Tradit Chin Med. 2025 Apr;45(2):376-384. doi: 10.19852/j.cnki.jtcm.2025.02.012.

ABSTRACT

OBJECTIVE: To investigate the mechanism underlying the effect of the Huanglian decoction (, HLD) on morphine tolerance (MT), using network pharmacology, and to verify these mechanisms in vitro and in vivo.

METHODS: Available biological data on each drug in the HLD were retrieved from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform. The target proteins of MT were retrieved from the GeneCards, PharmGkb, Therapeutic Target Database, DrugBank, and Online Mendelian Inheritance in Man databases. Information regarding MT and the drug targets was compared to obtain overlapping elements. This information was imported into the Search Tool for the Retrieval of Interacting Genes/Proteins platform to obtain a protein-protein interaction network diagram. Then, a "component-target" network diagram was constructed using screened drug components and target information, viaCytoscape (Institute for Systems Biology, Seattle, WA, USA). The database for annotation, visualization, and integrated discovery was used for Gene Ontology enrichment and Kyoto Encyclopedia of Genes and Genomes pathways analyses. Pathway information predicted by network pharmacology was verified using animal studies and cell experiments.

RESULTS: Network pharmacology analysis identified 22 active compounds of HLD and revealed that HLD partially ameliorated MT by modulating inflammatory, apoptosis, and nuclear factor kappa B (NF-κB) signaling pathways. Berberine (BBR), one of the main components of HLD, inhibited the development of MT in mice. BBR reduced cell viability while increasing B-cell lymphoma 2 (Bcl-2) protein expression and decreasing CD86, NF-κB, Bax, and Caspase-3 protein expression in brain vascular 2 (BV2) mcroglia cells treated with morphine. Additionally, BBR contributed to a reduction in pro-inflammatory cytokine release and apoptotic cell number.

CONCLUSIONS: BBR, a key component of HLD, effectively suppressed microglial activation and neuro-inflammation by regulating the NF-κB and apoptosis signaling pathways, thereby delaying MT. This study offers a novel approach to enhance the clinical analgesic efficacy of morphine.

PMID:40151124 | DOI:10.19852/j.cnki.jtcm.2025.02.012

Biomolecules. 2025 Mar 4;15(3):370. doi: 10.3390/biom15030370.

ABSTRACT

In the heart, Connexin 43 (Cx43) is involved in intercellular communication through gap junctions and exosomes. In addition, Cx43-formed hemichannels at the plasma membrane are important for ion homeostasis and cellular volume regulation. Through its localization within nuclei and mitochondria, Cx43 influences the function of the respective organelles. Several cardiovascular diseases such as heart failure, ischemia/reperfusion injury, hypertrophic cardiomyopathy and arrhythmias are characterized by Cx43 downregulation and a dysregulated Cx43 function. Accordingly, a putative therapeutic approach of these diseases would include the induction of Cx43 expression in the damaged heart, albeit such induction may have both beneficial and detrimental effects. In this review we discuss the consequences of increasing cardiac Cx43 expression, and discuss this manipulation as a strategy for the treatment of cardiovascular diseases.

PMID:40149906 | DOI:10.3390/biom15030370

Biomedicines. 2025 Mar 3;13(3):612. doi: 10.3390/biomedicines13030612.

ABSTRACT

Background: There is an urgent need to identify new biomarkers for early diagnosis and development of therapeutic strategies for diabetes mellitus (DM) patients who have invasive breast cancer (BC). We previously reported the increased activated form of 70 kDa ribosomal protein S6 kinase 1 (phospho-p70S6K1) in a triple-negative BC (TNBC) cell line MDA-MB-231 exposed to glycated albumin (GA) and in invasive ductal carcinoma tissues from T2DM patients, compared to untreated cells and their non-diabetic counterparts, respectively. Objective: We aimed to explore the function of p70S6K1 in GA-promoted TNBC progression. Methods: By employing small interference (si)RNA technology or blocking its kinase activity using its specific pharmacological inhibitor, we monitored cell invasion using Transwell® inserts and the expression levels of activated signaling proteins and cancer-related proteins using Western blot. Results: In silico analysis revealed that high mRNA levels of p70S6K1 were associated with an unfavorable prognosis and progression to advanced stages of TNBC in DM patients. The downregulation/blockade of p70S6K1 inhibited GA-promoted MDA-MB-231 cell invasion and the phosphorylation of protein S6 and ERK1/2, the p70S6K1 downstream effector, and the key oncogenic signaling protein, respectively. The suppression of the expression of GA-upregulated cancer proteins, including enolase-2, capping protein CapG, galectin-3, and cathepsin D, was observed after p70S6K1 downregulation/blockade. Further in silico validation analyses revealed increased gene expression of galectin-3 in DM TNBC patients, resulting in poor overall survival and disease-free survival. Conclusions: Targeting p70S6K1 may present a valuable therapeutic strategy, while galectin-3 could serve as a potential prognostic biomarker for invasive BC progression in DM patients.

PMID:40149589 | DOI:10.3390/biomedicines13030612

Genes (Basel). 2025 Feb 28;16(3):297. doi: 10.3390/genes16030297.

ABSTRACT

This study introduces a novel framework that simultaneously addresses the challenges of performance accuracy and result interpretability in transcriptomic-data-based classification. Background/objectives: In biological data classification, it is challenging to achieve both high performance accuracy and interpretability at the same time. This study presents a framework to address both challenges in transcriptomic-data-based classification. The goal is to select features, models, and a meta-voting classifier that optimizes both classification performance and interpretability. Methods: The framework consists of a four-step feature selection process: (1) the identification of metabolic pathways whose enzyme-gene expressions discriminate samples with different labels, aiding interpretability; (2) the selection of pathways whose expression variance is largely captured by the first principal component of the gene expression matrix; (3) the selection of minimal sets of genes, whose collective discerning power covers 95% of the pathway-based discerning power; and (4) the introduction of adversarial samples to identify and filter genes sensitive to such samples. Additionally, adversarial samples are used to select the optimal classification model, and a meta-voting classifier is constructed based on the optimized model results. Results: The framework applied to two cancer classification problems showed that in the binary classification, the prediction performance was comparable to the full-gene model, with F1-score differences of between -5% and 5%. In the ternary classification, the performance was significantly better, with F1-score differences ranging from -2% to 12%, while also maintaining excellent interpretability of the selected feature genes. Conclusions: This framework effectively integrates feature selection, adversarial sample handling, and model optimization, offering a valuable tool for a wide range of biological data classification problems. Its ability to balance performance accuracy and high interpretability makes it highly applicable in the field of computational biology.

PMID:40149449 | DOI:10.3390/genes16030297

Genes (Basel). 2025 Feb 27;16(3):293. doi: 10.3390/genes16030293.

ABSTRACT

Background/Objectives: microRNAs are small non-coding RNAs that regulate gene expression by inducing mRNA degradation or inhibiting translation. A growing body of evidence suggests that miRNAs may be utilized as anti-cancer therapeutics by targeting expression of key genes involved in cancerous transformation and progression. Renal cell cancer (RCC) is the most common kidney malignancy. The most efficient RCC treatments involve blockers of immune checkpoints, including antibodies targeting PD-L1 (Programmed Death Ligand 1). Interestingly, recent studies revealed the cross-kingdom horizontal transfer of plant miRNAs into mammalian cells, contributing to the modulation of gene expression by food ingestion. Here, we hypothesized that PD-L1 expression may be modulated by miRNAs originating from edible plants. Methods: To verify this hypothesis, we performed bioinformatic analysis to identify mes-miR395e from Manihot esculenta (cassava) as a promising candidate miRNA that could target PD-L1. To verify PD-L1 regulation mediated by the predicted plant miRNA, synthetic mes-miR395 mimics were transfected into cell lines derived from RCC tumors, followed by evaluation of PD-L1 expression using qPCR and Western blot. Results: Transfection of mes-miR395e mimics into RCC-derived cell lines confirmed that this miRNA decreases expression of PD-L1 in RCC cells at both mRNA and protein levels. Conclusions: This preliminary study shows the promise of plant miRNA as potential adjuvants supporting RCC treatment.

PMID:40149445 | DOI:10.3390/genes16030293

Genes (Basel). 2025 Feb 23;16(3):258. doi: 10.3390/genes16030258.

ABSTRACT

BACKGROUND/OBJECTIVES: Genes with similar expression patterns across multiple samples are considered coexpressed, and they may participate in similar biological processes or pathways. Gene coexpression networks depict the degree of similarity between the expression profiles of all genes in a set of samples. Gene coexpression tools allow for the prediction of functional gene partners or the assignment of roles to genes of unknown function. Weighted Gene Correlation Network Analysis (WGCNA) is an R package that provides a multitude of functions for constructing and analyzing a weighted or unweighted gene coexpression network.

METHODS: Previously preprocessed, high-quality gene expression data of 3500 samples of Affymetrix microarray technology from various tissues of the Arabidopsis thaliana plant model species were used to construct a weighted gene coexpression network, using WGCNA.

RESULTS: The gene dendrogram was used as the basis for the creation of a new Arabidopsis coexpression tool (ACT) version (ACT2.6). The dendrogram contains 21,273 leaves, each one corresponding to a single gene. Genes that are clustered in the same clade are coexpressed. WGCNA grouped the genes into 27 functional modules, all of which were positively or negatively correlated with specific tissues.

DISCUSSION: Genes known to be involved in common metabolic pathways were discovered in the same module. By comparing the current ACT version with the previous one, it was shown that the new version outperforms the old one in discovering the functional connections between gene partners. ACT2.6 is a major upgrade over the previous version and a significant addition to the collection of public gene coexpression tools.

PMID:40149410 | DOI:10.3390/genes16030258

Entropy (Basel). 2025 Mar 7;27(3):280. doi: 10.3390/e27030280.

ABSTRACT

The known laws of nature in the physical sciences are well expressed in the language of mathematics, a fact that caused Eugene Wigner to wonder at the "unreasonable effectiveness" of mathematical concepts to explain physical phenomena. The biological sciences, in contrast, have resisted the formulation of precise mathematical laws that model the complexity of the living world. The limits of mathematics in biology are discussed as stemming from the impossibility of constructing a deterministic "Laplacian" model and the failure of set theory to capture the creative nature of evolutionary processes in the biosphere. Indeed, biology transcends the limits of computation. This leads to a necessity of finding new formalisms to describe biological reality, with or without strictly mathematical approaches. In the former case, mathematical expressions that do not demand numerical equivalence (equations) provide useful information without exact predictions. Examples of approximations without equal signs are given. The ineffectiveness of mathematics in biology is an invitation to expand the limits of science and to see that the creativity of nature transcends mathematical formalism.

PMID:40149204 | DOI:10.3390/e27030280

Mol Neurodegener. 2025 Mar 28;20(1):38. doi: 10.1186/s13024-025-00826-z.

ABSTRACT

Amyotrophic Lateral Sclerosis (ALS) and Frontotemporal Dementia (FTD) are overwhelmingly linked to TDP-43 dysfunction. Mutations in TDP-43 are rare, indicating that the progressive accumulation of exogenous factors - such as cellular stressors - converge on TDP-43 to play a key role in disease pathogenesis. Post translational modifications such as SUMOylation play essential roles in response to such exogenous stressors. We therefore set out to understand how SUMOylation may regulate TDP-43 in health and disease. We find that TDP-43 is regulated dynamically via SUMOylation in response to cellular stressors. When this process is blocked in vivo, we note age-dependent TDP-43 pathology and sex-specific behavioral deficits linking TDP-43 SUMOylation with aging and disease. We further find that SUMOylation is correlated with human aging and disease states. Collectively, this work presents TDP-43 SUMOylation as an early physiological response to cellular stress, disruption of which may confer a risk for TDP-43 proteinopathy.

PMID:40149017 | DOI:10.1186/s13024-025-00826-z

New Phytol. 2025 Mar 27. doi: 10.1111/nph.70101. Online ahead of print.

ABSTRACT

Robinia pseudoacacia L. (black locust) is a nitrogen (N)-fixing legume tree with significant ecological and agricultural importance. Unlike well-studied herbaceous legumes, R. pseudoacacia is a perennial woody species, representing an understudied group of legume trees that establish symbiosis with Mesorhizobium. Understanding its genomic and transcriptional responses to nodulation provides key insights into N fixation in long-lived plants and their role in ecosystem N cycling. We assembled a high-quality 699.6-Mb reference genome and performed transcriptomic analyses comparing inoculated and noninoculated plants. Differential expression and co-expression network analyses revealed organ-specific regulatory pathways, identifying key genes associated with symbiosis, nutrient transport, and stress adaptation. Unlike Medicago truncatula, which predominantly responds to nodulation in roots, R. pseudoacacia exhibited stem-centered transcriptional reprogramming, with the majority of differentially expressed genes located in stems rather than in roots. Co-expression network analysis identified gene modules associated with "leghemoglobins", metal detoxification, and systemic nutrient allocation, highlighting a coordinated long-distance response to N fixation. This study establishes R. pseudoacacia as a genomic model for nodulating trees, providing essential resources for evolutionary, ecological, and applied research. These findings have significant implications for reforestation, phytoremediation, forestry, and sustainable N management, particularly in depleted, degraded, and contaminated soil ecosystems.

PMID:40149007 | DOI:10.1111/nph.70101

J Biol Eng. 2025 Mar 27;19(1):25. doi: 10.1186/s13036-025-00493-0.

ABSTRACT

Achieving consistent and predictable gene expression from plasmids remains challenging. While much attention has focused on intra-genetic elements like promoters and ribosomal binding sites, the spatial arrangement of genes within plasmids-referred to as gene syntax-also plays a crucial role in shaping gene expression dynamics. This study addresses the largely overlooked impact of gene syntaxes on gene expression variability and accuracy. Utilizing a dual-fluorescent protein system, we systematically investigated how different gene orientations and orders affect expression profiles including mean levels, relative expression ratios, and cell-to-cell variations. We found that arbitrary gene placement on a plasmid can cause significantly different expression means and ratios. Genes aligned in the same direction as a plasmid's origin of replication (Ori) typically exhibit higher expression levels; adjacent genes in the divergent orientation tend to suppress each other's expression; altering gene order without changing orientation can yield varied expression. Despite unchanged total cell-to-cell variation across different syntaxes, gene syntaxes can also influence intrinsic and extrinsic noise. Interestingly, cell-to-cell variation appears to depend on the reporter proteins, with RFP consistently showing higher variation than GFP. Moreover, the effects of gene syntax can propagate to downstream circuits, strongly affecting the performance of incoherent feedforward loops and contributing to unpredictable outcomes in genetic networks. Our findings reveal that gene syntaxes on plasmids modulate gene expression and circuit behavior, providing valuable insights for the rational design of plasmids and genetic circuits.

PMID:40148941 | DOI:10.1186/s13036-025-00493-0

Plant Cell Environ. 2025 Mar 27. doi: 10.1111/pce.15481. Online ahead of print.

ABSTRACT

Plant reactions to stress vary with development stage and fitness. This study assessed the relationship between light and chilling stress in Arabidopsis acclimation. By analysing the transcriptome and proteome responses of expanding leaves subjected to varying light intensity and cold, 2251 and 2064 early response genes and proteins were identified, respectively. Many of these represent as a yet unknown part of the early response to cold, illustrating a development-dependent response to stress and duality in plant adaptations. While standard light promoted photosynthetic upregulation, plastid maintenance, and increased resilience, low light triggered a unique metabolic shift, prioritizing ribosome biogenesis and lipid metabolism and attenuating the expression of genes associated with plant immunity. The comparison of early response in young leaves with that in expanded ones showed striking differences, suggesting a sacrifice of expanded leaves to support young ones. Validations of selected DEGs in mutant background confirmed a role of HSP90-1, transcription factor FLZ13, and Phospholipase A1 (PLIP) in response to cold, and the PLIP family emerged as crucial in promoting acclimation and freezing stress tolerance. The findings highlight the dynamic mechanisms that enable plants to adapt to challenging environments and pave the way for the development of genetically modified crops with enhanced freezing tolerance.

PMID:40148745 | DOI:10.1111/pce.15481

Nat Rev Genet. 2025 Mar 27. doi: 10.1038/s41576-025-00835-0. Online ahead of print.

NO ABSTRACT

PMID:40148574 | DOI:10.1038/s41576-025-00835-0

Nat Microbiol. 2025 Mar 27. doi: 10.1038/s41564-025-01954-4. Online ahead of print.

ABSTRACT

Every step in common microbiome profiling protocols has variable efficiency for each microbe, for example, different DNA extraction efficiency for Gram-positive bacteria. These processing biases impede the identification of signals that are biologically interpretable and generalizable across studies. 'Batch-correction' methods have been used to address these issues computationally with some success, but they are largely non-interpretable and often require the use of an outcome variable in a manner that risks overfitting. We present DEBIAS-M (domain adaptation with phenotype estimation and batch integration across studies of the microbiome), an interpretable framework for inference and correction of processing bias, which facilitates domain adaptation in microbiome studies. DEBIAS-M learns bias-correction factors for each microbe in each batch that simultaneously minimize batch effects and maximize cross-study associations with phenotypes. Using diverse benchmarks including 16S rRNA and metagenomic sequencing, classification and regression, and a variety of clinical and molecular targets, we demonstrate that using DEBIAS-M improves cross-study prediction accuracy compared with commonly used batch-correction methods. Notably, we show that the inferred bias-correction factors are stable, interpretable and strongly associated with specific experimental protocols. Overall, we show that DEBIAS-M facilitates improved modelling of microbiome data and identification of interpretable signals that generalize across studies.

PMID:40148567 | DOI:10.1038/s41564-025-01954-4

Leukemia. 2025 Mar 27. doi: 10.1038/s41375-025-02575-w. Online ahead of print.

ABSTRACT

Unbiased kinome-wide CRISPR screening identified DYRK1A as a potential therapeutic target in KMT2A-rearranged (KMT2A-R) B-acute lymphoblastic leukemia (ALL). Mechanistically, we demonstrate that DYRK1A is regulated by the KMT2A fusion protein and affects cell proliferation by regulating MYC expression and ERK phosphorylation. We further observed that pharmacologic DYRK1A inhibition markedly reduced human KMT2A-R ALL cell proliferation in vitro and potently decreased leukemia proliferation in vivo in drug-treated patient-derived xenograft mouse models. DYRK1A inhibition induced expression of the proapoptotic factor BIM and reduced the expression of BCL-XL, consequently sensitizing KMT2A-R ALL cells to BCL2 inhibition. Dual inhibition of DYRK1A and BCL2 synergistically decreased KMT2A-R ALL cell survival in vitro and reduced leukemic burden in mice. Taken together, our data establishes DYRK1A as a novel therapeutic target in KMT2A-R ALL and credential dual inhibition of DYRK1A and BCL2 as an effective translational therapeutic strategy for this high-risk ALL subtype.

PMID:40148558 | DOI:10.1038/s41375-025-02575-w

Nat Rev Nephrol. 2025 Mar 27. doi: 10.1038/s41581-025-00946-1. Online ahead of print.

ABSTRACT

The application of spatially resolved mass spectrometry (MS) and MS imaging approaches for studying biomolecular processes in the kidney is rapidly growing. These powerful methods, which enable label-free and multiplexed detection of many molecular classes across omics domains (including metabolites, drugs, proteins and protein post-translational modifications), are beginning to reveal new molecular insights related to kidney health and disease. The complexity of the kidney often necessitates multiple scales of analysis for interrogating biofluids, whole organs, functional tissue units, single cells and subcellular compartments. Various MS methods can generate omics data across these spatial domains and facilitate both basic science and pathological assessment of the kidney. Optimal processes related to sample preparation and handling for different MS applications are rapidly evolving. Emerging technology and methods, improvement of spatial resolution, broader molecular characterization, multimodal and multiomics approaches and the use of machine learning and artificial intelligence approaches promise to make these applications even more valuable in the field of nephology. Overall, spatially resolved MS and MS imaging methods have the potential to fill much of the omics gap in systems biology analysis of the kidney and provide functional outputs that cannot be obtained using genomics and transcriptomic methods.

PMID:40148534 | DOI:10.1038/s41581-025-00946-1

Sci Rep. 2025 Mar 27;15(1):10617. doi: 10.1038/s41598-025-93219-7.

ABSTRACT

Mesenchymal stem cell-derived exosomes exhibit promising potential in tissue regeneration. Recent studies highlight its significant therapeutic potential in various stages of wound healing. However, the clinical translation of exosome-based therapy was hindered due to issues regarding low productivity and the lack of efficient production protocol to obtain a clinically relevant exosome quantity. Therefore, this study established a potential upscaling protocol to produce exosomes derived from canine adipose-derived mesenchymal stem cells (cAD-MSCs) and explored its potential for wound treatment. The potential upscaling protocol, termed VSCBIC-3-3D, was carried out using VSCBIC-3 in-house serum-free exosome-collecting solution in a three-dimensional (3D) culture system followed by the tangential flow filtration (TFF) isolation. Our findings suggest that culturing cAD-MSCs with VSCBIC-3 maintained cell morphology and viability. Compared to conventional two-dimensional (2D) protocols, The potential upscaling protocol increased exosome yield and concentration in conditioned medium by 2.4-fold and 3.2-fold, respectively. The quality assessment revealed enhanced purity and bioactivity of exosomes produced using the VSCBIC-3-3D protocol. In addition, the cAD-MSCs-derived exosomes were shown to significantly improve fibroblast migration, proliferation, and wound healing-related gene expression in vitro. This study collectively demonstrates that potential upscaling protocol establishment allowed robust production of exosomes from cAD-MSCs, which exhibit therapeutic potential for wound healing in vitro.

PMID:40148423 | DOI:10.1038/s41598-025-93219-7

Nat Commun. 2025 Mar 28;16(1):3020. doi: 10.1038/s41467-025-58363-8.

ABSTRACT

Phosphorylase kinase (PhK) regulates the degradation of glycogen by integrating diverse signals, providing energy to the organism. Dysfunctional mutations may directly lead to Glycogen Storage Disease type IX (GSD IX), whereas the abnormal expression of PhK is also associated with tumors. Here, we use cryo-electron microscopy (cryo-EM) to resolve its near-atomic structures in the inactive and active states. These structures reveal the interactions and relative locations of the four subunits (αβγδ) within the PhK complex. Phosphorylated α and β subunits induce PhK to present a more compact state, while Ca2+ causes sliding of the δ subunit along the helix of the γ subunit. Both actions synergistically activate PhK by enabling the de-inhibition of the γ subunit. We also identified different binding modes between PhK and its substrate, glycogen phosphorylase (GP), in two distinct states, using cross-linking mass spectrometry (XL-MS). This study provides valuable insights into the regulatory mechanisms of PhK, thereby enhancing our understanding of GSD IX and its implications in tumorigenesis.

PMID:40148320 | DOI:10.1038/s41467-025-58363-8

Physiol Plant. 2025 Mar-Apr;177(2):e70181. doi: 10.1111/ppl.70181.

ABSTRACT

Oats (Avena sativa L) is a temperate cereal and an important healthy cereal cultivated for food and feed. Therefore, understanding drought responses in oats could significantly impact oat production under harsh climatic conditions. In particular, drought during anthesis (flowering) affects grain filling, quality and yield. Here, we characterised metabolite responses of two Mediterranean oat (Avena sativa L.) cultivars, Flega and Patones, during drought stress at anthesis. In the more drought-tolerant Patones, the developing grains from the top (older) and bottom (younger) spikelets of primary panicle were found to be larger in size in response to drought, suggesting accelerated grain development. Flega showed a more rapid transition to flowering and grain development under drought. The metabolomes of source (sheath, flag leaf, rachis) and sink (developing grains) tissues from Patones showed differential accumulation in fatty acids levels, including α-linolenic acid, sugars and amino acids with drought. Flega showed enhanced energy metabolism in both source and sink tissues. Lower levels of glutathione in source tissues and the accumulation of ophthalmic acid in the grains of Flega were indicators of oxidative stress. Our study revealed two distinct metabolite regulatory patterns in these cultivars during drought at anthesis. In Patones, α-linolenic acid-associated processes may accelerate grain-filling, while in Flega oxidative stress appears to influence traits such as flowering time. Overall, this work provides a first insight into the metabolite regulation in oat's source and sink tissues during anthesis under drought stress.

PMID:40148256 | DOI:10.1111/ppl.70181

J Sci Med Sport. 2025 Mar 5:S1440-2440(25)00062-3. doi: 10.1016/j.jsams.2025.02.009. Online ahead of print.

ABSTRACT

OBJECTIVES: Durability is emerging as a key performance determinant in cycling, but scarce evidence exists on the durability of female cyclists, and particularly on whether there are sex differences. We therefore aimed to determine potential sex differences in durability.

DESIGN: Observational field-based study.

METHODS: Power output data from training and competitions were registered in female and male professional cyclists (n = 42 each) during 1-5 seasons. Participants' highest power output values achieved for different effort durations (10 s, 1 min, 5 min, and 20 min) (or 'record power profile') were determined under non-fatigued conditions (0 kJ/kg) and after varying levels of accumulated work (10, 20 and 30 kJ/kg).

RESULTS: A significant reduction in the record power profile compared with non-fatigued conditions was observed after > 10 kJ/kg in both female and male cyclists (p < 0.001), with no significant impairment observed below this level of accumulated work (p > 0.05 for all). A similar relative decay (% decline compared with the fresh condition) was observed between sexes for 10-s efforts (p > 0.05). However, a significantly higher relative decay was observed in female cyclists after 20 kJ/kg for 1-min, 5-min, and 20-min efforts (4 %, 4 % and 2 %, respectively; p < 0.05), with these differences enlarging after 30 kJ/kg (8 %, 6 % and 7 %; p < 0.001).

CONCLUSIONS: Professional female cyclists show a greater relative decay in the record power profile after a given accumulated work compared to male cyclists, which might reflect a lower durability.

PMID:40148210 | DOI:10.1016/j.jsams.2025.02.009