Better biomarker analysis technologies can provide improvements in the detection, characterisation and monitoring of cancer and less invasive sampling of blood and other body fluids can improve acceptability and affordability. Here, we discuss these technologies with a specific focus on recent advances in electrochemical sensors, specifically for the analysis of extracellular vesicles (EVs). Widely used biomarker tests with relatively high sensitivity (e.g. ELISAs) are limited by their cost, storage requirements and shelf-life, and ease of use away from centralised facilities. Moreover, their limits of detection (most commonly in the nanomolar to picomolar, with new technologies pushing into the femtomolar range) remain challenged by low abundance biomarkers. Here, we discuss how electrochemical sensor platforms, although often requiring more effort to adapt for new analytes, can provide high sensitivity and direct quantitation at low cost. These platforms are also often simpler to use away from testing facilities. Additionally, we explore how EVs, by protecting nucleic acid and protein cargos from degradation, may facilitate the collective enrichment from blood samples of multiple tumour-derived biomarkers. Continued progress in analysis technologies, alongside a deeper understanding of biomarker biology and clinical value, holds the potential to improve outcomes for the increasing numbers of individuals diagnosed with cancer.

The vital role of brain-derived neurotrophic factor (BDNF) in neuronal development, synaptic plasticity, and neuroprotection has been explored for decades. Therefore, the expression, processing, and signalling activities of this neurotrophin, which is reliant upon TrkB and p75NTR receptors, have been well characterised in both health and disease. This review summarises the latest findings on BDNF dysregulation in neuropathologies. Indeed, across diseases of both the central and peripheral nervous systems, BDNF signalling is frequently disrupted, contributing to neuronal dysfunction and degeneration. Consequently, through direct or indirect enhancement of its expression and/or function, BDNF has proved to be a promising therapeutic target across many neurological conditions. However, the complexity of its regulation and interaction with several different receptors underpins the need for further research to deepen our understanding of BDNF disruption in neuropathologies and to achieve its therapeutic potential.

The continuing development and characterisation of human-induced pluripotent stem cell (hiPSC)-derived cell-types has opened up a virtually endless source of human, physiologically relevant cells, available at scale, for scientific research. The technology's maturation and refinement have allowed additional cell-types and sub-types to become available. The first step in adopting these novel cell-types is to properly characterise these cells and compare how they perform against the longer-established cell-types. Parallel to the progress in iPSC-derived cells has been the great strides in the platforms developed to assess and analyse the characteristics and functions of cells. These improved platforms have greatly increased the range, throughput and quality of the functional data that can be obtained from cell-types, including iPSC-derived cells. Research into cardiomyocytes in particular has been greatly enhanced by these platforms as cardiomyocytes not only have the expected cellular markers, proteomics and transcriptomics but are also electrically active and capable of contracting, opening a wide vista of potential assays. If human iPSC-derived cardiomyocytes are to confidently replace and supplement the existing animal and cellular models of the heart, it has to be demonstrated that they correctly replicate (or even improve) upon the functions and pharmacology of the existing heart models used on these new and improved platforms. Therefore, this review compares the functional and pharmacological differences seen between Axol's human iPSC-derived atrial and ventricular cardiomyocyte cells on a range of established and newer platforms demonstrating the advantages of using chamber-specific human iPSC-derived cardiomyocytes and discussing how their use could supplement these emerging techniques.

The triosephosphate isomerase (TIM)-barrel fold is one of the most versatile and ubiquitous protein folds in nature, hosting a wide variety of catalytic activities and functions while serving as a model system in protein biochemistry and engineering. This review explores its role as a key fold model in protein design, particularly in addressing challenges in stabilization and functionalization. We discuss historical and recent advances in de novo TIM barrel design from the landmark creation of sTIM11 to the development of the diversified variants, with a special focus on deepening our understanding of the determinants that modulate the sequence-structure-function relationships of this architecture. Also, we examine why the diversification of de novo TIM barrels toward functional diversification remains an open problem, given the absence of natural-like active site features. Current approaches have focused on incorporating structural extensions, modifying loops, and using cutting-edge AI-based strategies to create scaffolds with tailored characteristics. Despite significant advances, achieving enzymatically active de novo TIM barrels has been proven difficult, with only recent breakthroughs demonstrating functional activity. We discuss the limitations of stepwise design approaches and support integrated strategies that simultaneously optimize scaffold structure and active site shape, using both physics-based and AI-driven methods. By combining computational and experimental insights, we highlight the TIM barrel as a powerful template for custom enzyme design and as a model system to explore the intersection of protein biochemistry, biophysics, and design.

Poxviruses are double-stranded DNA viruses that infect a wide range of animals. Their large genomes encode for over 200 proteins and many of these help establish infection by inhibiting cell death or interfering with host antiviral signalling pathways. This includes the poxviral B cell lymphoma-2 (Bcl-2) proteins, which are found in most of the Chordopoxvirinae (vertebrate-infecting poxviruses), with individual viruses possessing multiple Bcl-2 proteins. These proteins are so named for the fact that they adopt an alpha helical bundle with structural similarity to cellular anti-apoptotic Bcl-2 proteins, despite lacking obvious primary amino acid sequence identity with these proteins. Not surprisingly, initial studies found that some poxviral Bcl-2 proteins inhibit apoptosis; however, it was soon clear that these proteins have additional functions. This brief review highlights some of these other activities that have either been more recently identified or for which additional mechanistic insight has been acquired. This includes the role of poxviral Bcl-2 proteins in modulating nucleotide-binding domain, leucine-rich repeat and pyrin domain-containing protein (NLRP) inflammasome activation and inhibiting antiviral signalling regulated by the interferon regulatory factor 3 and 7 (IRF3/7) transcription factors. Finally, we discuss how poxviral Bcl-2 proteins interfere with cellular antiviral TRIM family E3 ubiquitin-ligases to promote virus replication.

In all cells, hexameric helicases drive the unwinding of parental chromosomal DNA at replication forks to provide the single-stranded DNA templates required by replicative DNA polymerases. DNA unwinding proceeds via a steric exclusion mechanism in which the helicase encircles and translocates along one DNA strand while sterically excluding the opposite strand from its central channel. The details of how hexameric helicases translocate on single-stranded DNA remain incompletely understood and likely vary among species, as structural and mechanistic features-such as motor domain architecture and translocation polarity-shape helicase function. Recent high-resolution cryo-EM structures of the eukaryotic CMG (Cdc45-MCM-GINS) helicase, including complexes stalled at leading-strand G-quadruplexes, reveal two predominant DNA-bound conformations: planar and spiral. These structures show that different subsets of MCM subunits alternately engage the leading-strand template, defining intermediates of a nonrotary, hand-over-hand translocation mechanism. This mode of translocation differs from the sequential rotary hand-over-hand mechanism proposed for bacterial hexameric helicases, instead resembling that of other ring-shaped ATPase motors and can be described as a variant of the helical inchworm model. The evolution of this mechanism may reflect CMG's specialized role as a replisome organizer, enabling it to coordinate accessory factors and optimize replication fork progression. Together, these findings highlight the mechanistic diversity and evolutionary adaptability of hexameric helicases.

Mycobacterium tuberculosis (MTB) is the etiologic agent of tuberculosis (TB) in humans, an infectious disease that continues to be a significant global health concern. The long-term use of multiple anti-tubercular agents may result in patient non-compliance and increased drug toxicity, which could contribute to the emergence of drug-resistant MTB strains that are not susceptible even to second-line available drugs. It is therefore imperative that new antitubercular drugs and vaccines are developed. The peculiar traits of MTB, such as the biochemical and structural features of vital metabolic pathways, can be assessed to identify possible targets for drug development. Enzymes involved in pyrimidine metabolism may be suitable drug targets for TB, given that this pathway is essential for mycobacteria and comprises enzymes that differ from those found in humans. Here, we focused on reviewing the state of the art concerning the therapeutic opportunities presented by the pyrimidine biosynthetic pathway (PBP) as a potential source of enzymes that could be targeted for the treatment of TB. We selected essential enzymes belonging to the PBP for which we identified the existence of a drug discovery pipeline at both the preclinical and clinical levels. Moreover, we emphasize the biochemical and structural characteristics that are pertinent to the development of pharmaceutical agents. These include the molecular details that can ensure selectivity towards the pathogen’s proteins.

Aquaporins (AQPs) are crucial membrane proteins that primarily facilitate water transport across cell membranes. In the kidneys, AQP1, AQP7, AQP8, and AQP11 are expressed in the proximal tubules. AQP1 is also localized to the thin descending limb of the loop of Henle. AQP2, AQP3, AQP4, AQP5, and AQP6 are expressed in the collecting ducts. Specific AQPs, such as aquaglyceroporins and peroxiporins, also transport solutes like glycerol and hydrogen peroxide, indicating their broader physiological roles beyond water permeability. Renal AQPs play a fundamental role in urine concentration and maintaining water balance. However, some studies using AQP knockout mouse models have reported structural abnormalities in the renal tubules, along with defective water handling. These findings highlight the involvement of AQPs in regulating cell proliferation, migration, and apoptosis, which are essential processes for maintaining tubular integrity. Furthermore, aquaglyceroporins and peroxiporins are implicated in modulating cellular redox balance and contributing to oxidative stress responses that are also associated with tubular damage. This review explores how AQPs are regulated under physiological conditions and how they become dysregulated in kidney diseases such as acute kidney injury, diabetic kidney disease, and polycystic kidney disease. Understanding these mechanisms may help in identifying new therapeutic strategies targeting AQPs in renal pathologies.

Artificial intelligence (AI) has become a transformative tool in cell biology, driving discoveries through the analysis of complex biological data. This review explores the diverse applications of AI, including its impact on microscopy, imaging, drug discovery, and synthetic biology. AI methods have significantly advanced our ability to analyze cellular images at single-cell resolution, uncover complex patterns in biological data, and predict cellular responses to various stimuli. Deep learning approaches have improved cell segmentation and tracking, facilitated precise single-cell transcriptomics analysis, and enhanced our understanding of protein structures and interactions. The application of AI to high-throughput technologies has also enabled detailed modeling of cell behavior. Key challenges are addressed, such as data quality requirements, model interpretability, and the need to democratize AI tools for broader accessibility in biology. Finally, the review considers future directions, highlighting AI’s potential to advance basic research and therapeutic applications.