Pyruvate kinase M2 (PKM2), a key glycolytic enzyme, plays a pivotal role in cancer-associated metabolic reprogramming and is frequently over-expressed in several malignancies. Beyond its metabolic activities, PKM2 exhibits numerous non-metabolic functions, mediated through a complex interplay of allosteric regulation, post-translational modifications and macromolecular interactions. Cancer cells exploit these distinctive properties to sustain Warburg effect, supporting proliferation, survival and tumor progression, making PKM2 a potential therapeutic target. Different strategies have been employed to modulate PKM2 activity in cancer (stabilizing tetrameric ensemble or mitigating its dimeric form), however only a limited number of modulators have advanced successfully to clinical trials. This review summarizes multifaceted role of PKM2 beyond its cytoplasmic and nuclear functions, including its emerging role in exosomes, mitochondria and as RNA binding protein in tumorigenesis. Additionally it discusses cancer-associated PKM2 mutations and their impact on structure and function. It highlights current therapeutic approaches targeting PKM2, including small-molecule modulators, as well as alternative strategies, such as antisense oligonucleotides, peptides disrupting PKM2-associated macromolecular interactions, and allosteric converters. Finally, it addresses major challenges and limitations in targeting PKM2, its context-dependent functional plasticity across cancer hallmarks, and emphasizes how deeper understanding of its structure-function dynamics may facilitate the development of more effective cancer therapeutics.
DNA nanomachines leverage their high programmability, precise spatial addressability, and near-atomic structural control to overcome key limitations of conventional medical diagnostics. Through rational design, they enable highly specific biomarker recognition, amplification of low-abundance signals, and dynamic responses, thereby enhancing diagnostic sensitivity, speed, and accuracy. These capabilities open new avenues for early disease screening, classification, prognostic assessment, and emergency medical response. This review provides a comprehensive survey of the fundamental principles and working mechanisms of DNA nanomachines and the strategies for constructing functional devices and their applications in medical diagnostics, as well as current challenges and future directions.
The rapid pace of innovation in gene therapy has ushered in a new era of transformative medicine, as demonstrated by landmark clinical success in the rapid development and administration of the first personalized n-of-1 treatment for carbamoyl-phosphate synthetase 1 deficiency. While the therapeutic efficacy and safety profiles of these cutting-edge modalities have steadily improved, the primary barriers to their broad clinical translation are becoming increasingly clear. The most significant challenges are no longer confined to the on-target potency of the therapeutic itself; rather, they are rooted in the complexities of commercial formulation and the limitations of a traditional regulatory framework. The scientific progress in drug efficacy, while continuous and necessary, is now outpaced by the significant logistical and procedural hurdles of scaling production, ensuring product consistency, and navigating a regulatory landscape that was not designed for the unique characteristics of these one-time, patient-specific therapies. This review will explore how production bottlenecks, matters of market demand and regulatory compliance, as well as the perpetuation of traditional systemic incentives now stand as the predominant forces impeding the translatability of advanced gene therapies from bench to bedside and delve into the prevailing institutional strategies for providing its access to patients.
With few exceptions, all organisms on Earth use a common amino acid alphabet for synthesizing protein that consists of 20 canonical amino acids. Heterotrophic organisms have to obtain these amino acids from their food, especially the indispensable amino acids. The amount of and ratio between the indispensable amino acids is therefore a major determinant of protein quality. There exist several measures of protein quality for human nutrition and all of them rely on the empirical estimation of amino acid requirements. With the availability of whole genome sequencing data, however, a new method of deductively deriving amino acid requirements became available which uses the information encoded on the exome (the totality of protein-coding exons). By translating an organism's exome into the corresponding proteome in silico, the average encoded amino acid pattern can be computed and used ex hypothesi for defining an ideal amino acid pattern. Here I review the theoretical concepts behind exome-matched proteins and summarize the preclinical data that provide preliminary evidence for the hypothesis that such proteins indeed constitute an ideal protein source to maximize growth, reproduction and health. While clinical trials are yet to confirm this hypothesis in humans, there is a broad hypothetical range of applications of exome-matched proteins for human consumption. This review concludes that the concept of exome-matched proteins is interesting theoretically, promising for practical applications in animal and human nutrition and stimulating for further transdisciplinary research.
Finding microbial matter in tumors is one thing and deciding whether it matters is another. We frame the problem through biophysical niche constraints, evidence-tier grading, and the translational distance between biological plausibility and clinical readiness. The bar for moving from detection to biological claim varies by cancer type. In oral, colorectal, and pancreatic cancers, selected spatial and functional studies have moved beyond taxonomic cataloguing toward spatially localized host-microbe evidence within the tumor microenvironment, although the depth of validation varies substantially across studies and tumor types (Galeano Niño et al., 2022; Aykut et al., 2019; Nejman et al., 2020). For many other tumor types, low-biomass sequencing continues to outpace direct validation, and the signal-to-noise problem remains a central interpretive challenge (Dohlman et al., 2026; Vella and Rescigno, 2025). DNA damage, host signaling, immune remodeling, and metabolite exchange serve as the strongest mechanistic links involved, with the most developed examples concentrated in gastrointestinal and mucosa-adjacent tumors. Yet translational claims frequently treat sequencing-based observations as carrying comparable weight to localized intratumoral proof, conflating evidentiary categories that require different standards of support. Throughout this review, we evaluate spatial localization, contamination risk, and the distance between biological plausibility and clinical readiness as central interpretive criteria, and we argue that well-supported ecological signals presently inform more reliably than long catalogs assembled from uneven evidentiary classes.
The propagating nerve impulse is universally recorded as an electrical event, and the Hodgkin-Huxley cable framework describes this event with remarkable quantitative fidelity. However, the same propagating impulse is accompanied by mechanical and thermal changes and travels through an axon that is never a bare membrane but a structured, ensheathed conduit. This review asks a deliberately physical question: how does the impulse travel along the fibre? We survey the correlates of conduction in one physical dimension at a time, namely electrical, mechanical, thermal, and structural, together with the constraint imposed by the spatial extent of the active region, and we set the principal proposed frameworks beside the classical one, where each is relevant to a given phenomenon. The aim is to organise the available data, to ask which physical substrate would integrate them, and to commit, in a calibrated form, to the reading that this survey undertakes to develop.
Pregnancy disorders, including preeclampsia, gestational diabetes mellitus, and intrauterine growth restriction, represent a significant global burden of maternal and neonatal morbidity and mortality. Early and accurate detection of these conditions remains a critical clinical challenge, as conventional diagnostic methods often lack the sensitivity and specificity required for timely intervention. Blood-based biomarkers have emerged as a promising avenue for non-invasive surveillance; however, their full diagnostic potential is only now being realized through the application of advanced biophysical analytical techniques. This review examines three advanced methodological approaches - differential scanning calorimetry (DSC), atomic force microscopy (AFM), and microfluidic analysis - as applied to the characterization of blood-based indicators in pregnancy-related disorders. DSC enables thermodynamic profiling of plasma proteomes, revealing disorder-specific denaturation signatures that reflect systemic pathophysiological alterations. AFM provides nanoscale structural and mechanical interrogation of red blood cells, platelets, and plasma proteins, uncovering morphological and viscoelastic changes associated with hemostatic dysregulation and endothelial dysfunction. Microfluidic platforms offer high-throughput, minimally invasive analysis of whole blood rheology, cellular deformability, and biomarker concentrations under physiologically relevant flow conditions. Collectively, these approaches provide complementary and multi-dimensional characterization of the maternal blood milieu that transcends the limitations of conventional biochemical assays. We discuss the current state of evidence, methodological advances, translational barriers, and future directions for integrating these biophysical strategies into point-of-care diagnostic frameworks. The convergence of these technologies holds considerable promise for transforming prenatal screening and enabling precision management of high-risk pregnancies.
Background Atmospheric and underground nuclear weapons testing generated long-lasting radioactive contamination across multiple terrestrial and marine environments. Several former nuclear test sites still exhibit heterogeneous distributions of radionuclides in soils, groundwater, sediments, and biota decades after testing ceased. Objective This review critically examines radionuclide persistence, environmental transfer processes, and reported ecological and plant-related responses across major historical nuclear test regions, including the Nevada Test Site, Semipalatinsk, the Marshall Islands and French Polynesia. Methods A comparative literature-based analysis was conducted using radiological surveys, environmental monitoring reports, and peer-reviewed radioecological studies. The review evaluated contamination patterns, soil-to-biota transfer pathways, and documented ecological observations across chronically exposed environments. Results Persistent contamination involving radionuclides such as 137Cs, 90Sr, plutonium isotopes, americium, and tritium remain documented at several former testing areas. Monitoring programs consistently report strong spatial heterogeneity influenced by local geology, hydrology, atmospheric transport, and resuspension processes. Although some studies describe altered ecological dynamics and physiological stress responses in exposed organisms, evidence for consistent long-term ecosystem-scale effects or adaptive biological responses remains limited and site-dependent. Interpretation is further complicated by heterogeneous dosimetry, limited longitudinal datasets, and multiple environmental confounding factors. Conclusions Former nuclear test sites remain important environments for long-term radioecological investigation. Current evidence clearly supports persistent environmental contamination and ongoing radionuclide transfer processes, whereas broader ecological consequences remain incompletely resolved.
Cancer cells undergo extensive functional, morphological, and genetic alterations that profoundly affect proliferation, metabolism, differentiation, and communication with the surrounding microenvironment.In this context, reciprocal exchanges with the extracellular milieu play a pivotal role. These processes are mediated by membrane transport proteins collectively referred to as the “transportome”, including both plasma membrane transporters and those localized to intracellular compartments that regulate trafficking between organelles.In many cancers, the transportome undergoes extensive remodeling, ranging from altered gene expression to the generation of distinct protein isoforms. These changes are driven by multiple direct and indirect epigenetic mechanisms, including DNA methylation, histone modifications, and non-coding RNA activity.Here, we review the rapidly expanding body of literature addressing the epigenetic regulation of the transportome in cancer, with particular emphasis on the growing number of cases in which epigenetic modulation has been demonstrated or strongly suggested. Although this field is still in its early stages, further mechanistic investigation and comprehensive characterization of these processes will be essential to fully elucidate their biological and clinical relevance.Ultimately, such advances may contribute to the development of more personalized therapeutic strategies, with the potential to improve efficacy while reducing the side effects associated with conventional treatments.
Articular cartilage homeostasis relies on chondrocytes to maintain extracellular matrix (ECM) integrity, with fluid shear stress (FSS) emerging as a critical regulator of chondrocyte function. Osteoarthritis (OA), a leading cause of global disability, is driven by abnormal mechanical loading, yet the dual role of FSS in joint health and disease remains incompletely defined, and existing reviews have not fully integrated its biphasic dose-effect boundaries, mechanotransduction networks, and translational pathways within a unified framework. To address this gap, we synthesize evidence that FSS exerts biphasic control over chondrocyte biology: physiological FSS, operationally approximated as low-to-moderate laminar shear stress within 0.5-10 Pa in many in vitro models, sustains cartilage homeostasis via anabolic pathways (ERK5, PI3K/Akt, AMPK) that promote ECM synthesis, cell proliferation, and cytoprotection; in contrast, pathological FSS, often exceeding approximately 10-15 Pa or occurring as prolonged continuous/turbulent shear or under inflammatory conditions, triggers catabolic and pro-inflammatory responses (NF-κB, JNK, Hippo/YAP) recapitulating OA phenotypes, including ECM degradation and chondrocyte apoptosis. Mechanotransduction of FSS involves conserved sensors (Ca2+ channels, integrins, cytoskeleton) and extensive crosstalk between signaling networks and additional regulation by non-coding RNAs, thereby providing an integrated mechanosensory-to-transcriptional framework for interpreting FSS-dependent chondrocyte responses. Translating this duality, FSS-based strategies, from tissue engineering bioreactors to targeted inhibition of pathological pathways and mechanical interventions, hold promise for OA therapy, providing an integrated framework for clinical translation. However, context dependency of FSS effects, microenvironmental heterogeneity, and signaling redundancy remain barriers to clinical translation. Resolving these challenges via biomimetic models and multidisciplinary approaches will advance precision medicine for OA by harnessing FSS's therapeutic potential while mitigating its pathological contributions.
Ventricular assist devices (VADs) integrate multiple branches of applied mechanics within a single implanted system, spanning rotor-scale haemodynamics, nonlinear ventricular wall mechanics, blood trauma, and closed-loop control under changing physiological loads. This review aims to unify five mathematical frameworks central to VAD modelling: ventricular mechanics, blood rheology and damage, partial differential equation (PDE)-based device haemodynamics, pump engineering, and nonlinear heart-device dynamics. By bringing these domains together, the review clarifies their interactions and highlights unresolved mathematical challenges that limit progress in design, control, and prediction. An expository narrative review was conducted in accordance with the Scale for the Assessment of Narrative Review Articles (SANRA); a completed SANRA checklist is provided as Supplementary Material. Relevant literature was identified through targeted searches of PubMed, Scopus, and Web of Science, supplemented by citation tracking. Studies were selected for mathematical relevance, with emphasis on formulations that recur across VAD research, reveal model limitations, or connect analytical structure to clinically important complications. Major LVAD complications, including pump thrombosis, haemolysis, suction instability, and acquired von Willebrand syndrome, map onto distinct but interacting mathematical domains. Important cross-disciplinary links emerge between statistical mechanics and continuum damage models, between bifurcation theory and proportional-integral controller design, and between reduced-order cardiovascular models and full fluid-structure interaction simulations. Several formulations currently used in clinical, or engineering practice appear to extend beyond their original validation range. The mathematical problems underlying VAD therapy are strongly coupled and, in several areas, remain open. Advances in fluid-structure interaction theory, first-principles haemolysis modelling, and bifurcation analysis of the heart-pump oscillator could substantially improve device design, controller safety, and clinical outcome prediction.
Brahma-associated factor 57 (BAF57), known as SWI/SNF matrix-associated actin-dependent regulator of chromatin subfamily E member 1 (SMARCE1), is a main subunit ubiquitously existing in mammalian SWI/SNF ATP-dependent chromatin remodeling complexes. BAF57 regulates diverse biological processes, including gene transcription, DNA recombination, repair, and replication. It plays a critical role in cell cycle control, cellular growth and development, skeletal muscle differentiation, and immune modulation. Beyond its fundamental biological functions, BAF57 was identified as a potential biomarker for diagnosing and monitoring tumor-related, neurodegenerative, and inflammatory disorders. In recent years, BAF57/SMARCE1 has attracted increasing attention as a biomarker and a therapeutic target for various diseases. This review systematically summarizes the structural characteristics, biological functions, and disease associations of BAF57/SMARCE1, and discusses its emerging applications and future prospects in clinical diagnosis and treatment.
Over the past two decades, photonic sensing has transitioned from laboratory concepts to clinically relevant tools for disease detection and treatment guidance, driven by the convergence of nanotechnology, artificial intelligence (AI), and advanced fabrication. Unlike recent reviews that focus narrowly on individual technologies, this Perspective synthesizes advances across silicon photonics, nanophotonics, and quantum platforms, highlighting their accelerating clinical translation. We present a unified framework showing how optical imaging, photoacoustic techniques, and quantum sensing address critical challenges in quality control, cell tracking, and toxicity monitoring-with particular emphasis on CAR-T cell therapy. The integration of microfluidics, AI-driven data analysis, and closed-loop therapeutic systems is enabling real-time, personalized interventions. However, we also provide a balanced assessment of the significant practical limitations of quantum and other emerging platforms, acknowledging that classical photonics remains sufficient and often more practical for most near-term applications. We further identify key translational barriers-including biocompatibility, regulatory pathways, system-level integration, surface fouling, reimbursement, and data integration-and propose strategies to overcome them. We conclude by defining four Grand Challenges for the next decade and presenting a technology roadmap with explicit timelines. The coming decade will likely see widespread clinical deployment of photonic sensors for point-of-care diagnostics, continuous monitoring, and image-guided interventions, including cell therapy workflows, ultimately improving patient outcomes.
Triggering receptor expressed on myeloid cells 2 (TREM2) is a central regulator of microglia activation and lipid metabolism, linking immune signaling to neurodegenerative and metabolic disease. While experimental and clinical studies have greatly expanded our understanding of TREM2 biology, the molecular principles governing its conformational plasticity, interactions with membranes and ligands, and the behavior of disease-associated variants remain unresolved. Recent molecular dynamics (MD) simulations of TREM2 have provided an atomistic view of these mechanisms, revealing novel structural, dynamic, and energetic features inaccessible to experimental methods alone. In this Review, we comprehensively assess these MD studies, integrating mechanistic insights across protein domains and modeling approaches. We critically evaluate simulations that describe how missense mutations uniquely perturb TREM2's complementarity-determining region (CDR) ligand-binding sites, transmembrane domain signaling motifs, and multimerization interfaces. We further elucidate how simulations capture novel CDR2 dynamics that cannot be resolved using traditional experimental methods, and how in silico findings align with data from experimental binding assays and crystallographic studies. Finally, we outline how rigorously designed simulations—performed with sufficient replicates and timescales—can guide rational engineering of small-molecule and peptide modulators targeting TREM2, advancing therapeutic strategies that can restore TREM2-mediated lipid sensing and signaling in metabolic and neurodegenerative diseases.
With the acceleration of global population aging, joint diseases such as osteoarthritis have become a major public health issue leading to disability among the elderly population. As a core treatment for joint damage, total joint replacement surgery has experienced continuously growing clinical demand. Traditional ex vivo testing methods, constrained by static and single-load analysis models, fail to realistically replicate the mechanical responses and progressive damage processes of artificial joints within complex physiological environments. This limitation has become a critical bottleneck restricting improvements in long-term performance and clinical optimization of implants. In situ mechanical characterization techniques, offering advantages of real-time and multiscale testing, provide a key technological pathway to overcome this challenge. This review outlines the development trajectory and research advancements in in situ mechanical characterization-driven testing technologies for artificial joints. It compares principles, core advantages, limitations, and application scenarios of various in situ characterization techniques across three pivotal dimensions: the in situ micro-characterization framework, in situ testing of effective properties in porous structures, and interfacial wear behavior and service failure mechanisms. The study elaborates on how in situ mechanical characterization drives material selection, structural optimization, and biomechanical mechanism analysis for artificial joints. Research indicates that modern characterization techniques enable comprehensive multiscale characterization spanning from atomic to macroscopic dimensions, effectively revealing the evolution of permeability in porous structures, dynamic mechanical responses of biomaterials, interfacial wear mechanisms, and failure progression pathways under complex loading conditions during physiological service. This provides methodological support and theoretical foundations for optimizing implant performance and evaluating long-term service safety. Additionally, the review identifies core challenges in clinical translation of current in situ testing technologies and envisions future development directions emphasizing multimodal integration and experimental-numerical coupling, thereby offering a reference framework for subsequent research in this field.
Ferroptosis is an iron dependent form of regulated cell death driven by excessive lipid peroxidation and implicated in numerous pathological conditions. While current research has largely focused on lipid metabolism and antioxidant systems, the contribution of upstream disturbances in protein homeostasis remains insufficiently integrated into ferroptosis frameworks. p62 is a multifunctional adaptor protein involved in ubiquitin mediated proteostasis, selective autophagy, and redox signaling. Emerging evidence indicates that alterations in p62 turnover occur under cellular stress conditions associated with ferroptosis and influence the Keap1-Nrf2 (NFE2L2) signaling axis, thereby linking proteostasis imbalance to redox regulation. However, the functional implications of this interaction remain fragmented across experimental systems. In this review, we integrate recent findings on the p62-Keap1-Nrf2 pathway in ferroptosis related processes, emphasizing its roles in redox buffering, autophagic flux, and cellular stress adaptation. Rather than directly executing ferroptosis, the p62-Keap1-Nrf2 axis is better understood as a regulatory system linking proteostasis to redox balance. We propose a conceptual framework in which ferroptosis emerges from a dynamic balance between proteostasis integrity, redox buffering capacity, iron metabolism, and lipid oxidative stress.
Hemostasis and thrombosis involve tightly regulated biological processes that operate near critical activation thresholds across molecular, cellular, mechanical, and biochemical scales. Traditional descriptions of coagulation emphasize deterministic cascade models; however, increasing evidence indicates that variability and stochastic dynamics substantially influence activation probability. This review outlines a conceptual multiscale biophysical framework that connects published experimental and computational findings on transcriptional bursting, platelet mechanotransduction, force-dependent receptor stabilization, and spatiotemporal thrombin propagation. At the molecular level, stochastic promoter switching generates fluctuations in protein abundance, shaping the probability of exceeding functional concentration thresholds. At the cellular scale, nanoscale surface architecture and receptor density modulate the time required for integrin clustering under shear flow, thereby altering adhesion stability. At the receptor-ligand interface, tensile force reshapes energy landscapes, producing catch-bond behavior that enhances bond lifetime within defined force regimes as demonstrated in prior molecular dynamics simulations. At the biochemical level, thrombin generation and fibrin polymerization exhibit nonlinear reaction-diffusion dynamics, where activation depends on crossing a critical concentration threshold. These processes can be unified via first-passage concepts, in which pathological activation corresponds to probabilistic boundary crossing rather than simple elevation of mean biomarker levels. This perspective shifts emphasis toward distributional properties, temporal variability, and amplification kinetics. By integrating stochastic modeling with published experimental data, this framework provides a mechanistic basis for understanding interindividual variability in thrombotic risk and suggests new avenues for quantitative risk assessment and therapeutic intervention. We emphasize that the framework presented here is conceptual and integrative rather than fully parameterized; we identify the quantitative parameters and cross-scale measurements that would be required to construct a fully predictive model in future work.
NLRs (NOD-like receptors) and their STAND (signal transduction ATPases with numerous domains) homologs represent a class of widespread, sophisticated signaling hubs, which function as allosteric switches to control various biological processes, including immune responses, apoptosis, tumorigenesis, cell stemness, gene expression, DNA damage repair and plant pathogen resistance. Over the past two decades, remarkable progress in structural studies has generated a wealth of data on these proteins. However, while the regulation of these allosteric switches encompasses both structural conformations and thermodynamic properties, the latter aspect remains largely unexplored. This review begins with a brief overview of recent advances in their structural and allosteric regulation, with a particular focus on how the decreased enthalpy and increased entropy likely drive the OFF-to-ON switching. Furthermore, the varying Shannon entropies during OFF-to-ON switching suggest that the fidelity of these molecular switches is never absolute but rather adapts to evolving conditions. The analyses and discussions offer new insights into how biochemical, thermodynamic, and informatic principles act in concert to shape cellular signaling, and potentially guide the future design of synthetic biochemical switches.
