Editor’s Choice Articles

Background: Tandem leucine-rich repeats (LRRs) are typically classified into eleven types; however, several variant motifs have also been reported. Here, we identified new LRR variants that exhibit dual characteristics of two distinct types. We investigated how the dual characteristics influence the structure and function of LRRs. Methods: We conducted sequence similarity searches using the protein database and analyzed sequence features. We also characterized the structural features of these LRR variant motifs using solved structures and AlphaFold models and investigated their potential biological functions through domain analysis. Results: Of the identified 3222 proteins, approximately 60% originate from the bacterial PVC superphylum. The variants were classified into two groups: one defined by the consensus sequence LxxLxLxx(C/T)xzI TDxxLxx(L/F)xx(L/C)xx, and the other by LxxLxLxxCxxI TDxxLxxLxxLP (where “z” denotes a deletion). The LRRs highly similar to the variants are occasionally observed in solved structures and comprise three types of super-secondary structures (SSSs): β-strand–α-helix adjoining a 3(10)-helix–β-strand, β-strand–3(10)-helix–β-strand, and β-strand–3(10)-helix adjoining an α-helix–β-strand. The AlphaFold models adopt these SSSs and, in addition, include the SSS of the β–α–β motif. Functional annotation identified kinase and F-box domains in a subset of these LRR proteins. Conclusions: The coexistence of these four SSSs and the high frequency of the first SSS appear to reflect the dual characteristics of the LRR variants. The LRR variant-containing proteins suggest potential roles in bacterial immunity and ubiquitination. The present findings expand the structural diversity of LRR proteins and provide new insights into their functional roles. Full article

This study addresses two key challenges in computational pharmacology: identifying novel therapeutic uses for existing drugs and modeling drug safety-related characteristics. We propose a multi-relational biomedical knowledge graph that integrates gene, drug, and disease associations with adverse effect data, enabling joint modeling of therapeutic and safety-related properties. A Relational Graph Convolutional Network (R-GCN) is employed to learn relationally aware embeddings that capture complex biological interactions across heterogeneous entities. The framework is evaluated on two tasks: (1) drug–disease link prediction for drug repurposing and (2) prediction of drug side-effect burden based on adverse event patterns. The experimental results demonstrate that the R-GCN model outperforms baseline methods, achieving 94.63% accuracy in drug–disease link prediction, while embedding-based classifiers attain up to 97.14% F1-score in side-effect burden classification. Additionally, multi-hop relational reasoning enables the discovery of biologically plausible connections between drugs, genes, and diseases. These findings highlight the effectiveness of knowledge graph-based representation learning in jointly supporting therapeutic discovery and safety-related analysis. While side-effect burden is used as a surrogate measure rather than a direct indicator of drug quality, the proposed framework provides a scalable foundation for integrating real-world pharmacovigilance and regulatory data in future studies. Full article

Paediatric ovarian neoplasms are rare and histologically diverse tumours with distinct clinical behaviour and prognosis compared to their adult counterparts. This review synthesises current knowledge from an anatomical pathology perspective, emphasising diagnostic and therapeutic strategies. Paediatric ovarian tumours are classified into three main categories: germ cell tumours, sex cord-stromal tumours, and epithelial neoplasms. Germ cell tumours, the most frequent in children, include dysgerminoma, mature and immature teratoma, yolk sac tumour, and choriocarcinoma. Sex cord-stromal tumours encompass Sertoli-Leydig cell tumours, juvenile granulosa cell tumours, and adrenal-like stromal tumours, while epithelial tumours, rare in paediatric patients, include serous and mucinous adenocarcinomas or cystadenomas. Clinical presentation is often nonspecific, with abdominal pain, pelvic mass, or endocrine abnormalities. Diagnosis integrates imaging, serum tumour markers, and histopathology supported by immunohistochemistry. Treatment prioritises fertility-sparing surgery, with selective adjuvant chemotherapy based on histotype and stage. Despite generally favourable outcomes, the rarity of these tumours limits high-quality evidence, highlighting the need for referral centres and multicenter studies. Standardised diagnostic protocols and personalised therapeutic approaches are essential to optimising clinical outcomes and preserve long-term reproductive function. Full article

Background/Objectives: Lactic acid bacteria have long been recognized as pivotal microorganisms in food fermentation and health promotion. However, their significance has recently grown due to innovative applications in various fields, particularly at the intersection of biotechnology and nanotechnology. This study aimed to provide a comprehensive overview of these emerging applications. Methods: The latest scientific literature was drawn from online databases and thoroughly reviewed. The new nomenclature system based on the post-2020 reclassification was used for reports. Results: The current study highlighted the evolving role of lactic acid bacteria, beyond their traditional use as starter cultures for food fermentation, in newer challenges, including the production of high-value bioactive compounds through bioprocessing under optimal conditions to enhance the yield, underlining the involved genes and pathways. Furthermore, this review addressed the beneficial effects of lactic acid bacteria as probiotics, postbiotics, and paraprobiotics in the treatment of various diseases and disorders, their application in the production of functional foods, and the encapsulation of their bioproducts to produce advanced health-promoting functional ingredients. The potential use of lactic acid bacteria to synthesize metallic nanoparticles, minicells, and carbon dots was also explored, promising significant advancements in nanomedicine. Conclusions: This review could open a new horizon for leveraging the potential of lactic acid bacteria in biotechnology, food science, and nanomedicine. The multilateral perspective offered here would provide a foundation for future research and development to exploit the capabilities of lactic acid bacteria across these innovative fields. Full article

Alzheimer’s disease (AD) signifies a devastating impact on the quality of life of patients and their families. At a biomolecular level, AD is characterized by the deposition of extracellular plaques of β-amyloid (Aβ), affecting language, spatial navigation, recognition abilities and memory. Among the selected 30 articles about polyoxometalates (POMs) and AD published from 2011 to 2025, pure POMs, hybrid POMs and POM nanoparticles can be found. The majority of POMs are polyoxotungstates (62%), the Keggin-type SiW₁₁O₃₉ being the most studied in AD. The main effect described is the inhibition of Aβ aggregates. Other effects include reversing the neurotoxicity induced by Aβ aggregates, decreasing ROS production and neuroinflammation, restoring memory and sequestering Zn²⁺ and Cu²⁺, among others, features that are well known to be associated with the pathology of AD. POMs have also shown the ability to induce the disaggregation of Aβ fibrils, particularly after irradiation, and to inhibit acetylcholinesterase activity at an nM range. Putting it all together, this review highlights a predominant trend in the exploration of POMs to act directly at the level of the formation and/or disaggregation of Aβ aggregates in the treatment of AD. Full article

Oxidative stress and inflammation are deeply interconnected processes implicated in the onset and progression of numerous chronic diseases. Despite promising mechanistic insights, conventional antioxidant and anti-inflammatory therapies such as NSAIDs, corticosteroids, and dietary antioxidants have shown limited and inconsistent success in long-term clinical applications due to challenges with efficacy, safety, and bioavailability. This review explores the molecular interplay between redox imbalance and inflammatory signaling and highlights why conventional therapeutic translation has often been inconsistent. It further examines emerging strategies that aim to overcome these limitations, including mitochondrial-targeted antioxidants, Nrf2 activators, immunometabolic modulators, redox enzyme mimetics, and advanced delivery platforms such as nanoparticle-enabled delivery. Natural polyphenols, nutraceuticals, and regenerative approaches, including stem cell-derived exosomes, are also considered for their dual anti-inflammatory and antioxidant potential. By integrating recent preclinical and clinical evidence, this review underscores the need for multimodal, personalized interventions that target the redox-inflammatory axis more precisely. These advances offer renewed promise for addressing complex diseases rooted in chronic inflammation and oxidative stress. Full article

Personalized cancer vaccines are a promising immunotherapy targeting patient-specific tumor neoantigens, yet their design and efficacy remain challenging. Recent advances in artificial intelligence (AI) provide powerful tools to enhance multiple stages of cancer vaccine development. This review systematically evaluates AI applications in personalized cancer vaccine research over the past five years, focusing on four key areas: neoantigen discovery, codon optimization, untranslated region (UTR) sequence generation, and mRNA vaccine design. We examine AI model architectures (e.g., neural networks), datasets (from omics to high-throughput assays), and outcomes in improving vaccine development. In neoantigen discovery, machine learning and deep learning models integrate peptide–MHC binding, antigen processing, and T cell receptor recognition to enhance immunogenic neoantigen identification. For sequence optimization, deep learning models for codon and UTR design improve protein expression and mRNA stability beyond traditional methods. AI-driven strategies also optimize mRNA vaccine constructs and formulations, including secondary structures and nanoparticle delivery systems. We discuss how these AI approaches converge to streamline effective personalized vaccine development, while addressing challenges such as data scarcity, tumor heterogeneity, and model interpretability. By leveraging AI innovations, the future of personalized cancer immunotherapy may see unprecedented improvements in both design efficiency and clinical effectiveness. Full article

The elderly population is growing worldwide. Non-steroidal anti-inflammatory drugs (NSAIDs) are commonly prescribed, but their adverse events can pose significant risks. Different NSAID molecules can exhibit varying risk profiles. This study aims to evaluate the cardiovascular, gastrointestinal, and renal safety profiles of ibuprofen, naproxen, acemetacin, diclofenac, celecoxib, and etoricoxib in elderly patients. A comprehensive literature search was conducted in PubMed and Cochrane Library. For the selection of articles, we used Medical Subject Headings (MeSH) terms “aged” sequentially and together with “ibuprofen”, “diclofenac”, “naproxen”, “acemetacin”, “celecoxib”, and “etoricoxib”. To assess the quality and interest of the articles, four independent reviewers screened titles and abstracts to identify potentially eligible studies. Strength of Recommendation Taxonomy (SORT) was used to rate the quality of individual studies and to establish recommendation strengths (RS). From 2086 articles identified, 39 studies met the inclusion criteria. Twenty studies analyzed cardiovascular safety, fourteen gastrointestinal safety, and four renal safety. When CV risk is the main concern celecoxib or naproxen are a good first choice (RS B). In high GI risk addition of PPI to naproxen or celecoxib use should be recommended (RS A). When renal function is on focus, celecoxib remains as first line of therapy (RS A). Diclofenac in the geriatric population should be avoided (RS B). Celecoxib is a good choice for elderly patients for whom it is difficult to direct pain treatment based on a single known risk factor (RS B). Full article

Metabolites are at the end of the gene–transcript–protein–metabolism cascade. As such, metabolomics is the omics approach that offers the most direct correlation with phenotype. This allows, where genomics, transcriptomics and proteomics fail to explain a trait, metabolomics to possibly provide an answer. Complex phenotypes, which are determined by the influence of multiple small-effect alleles, are an example of these situations. Consequently, the interest in metabolomics has increased exponentially in recent years. As a newer discipline, metabolomic bioinformatic analysis pipelines are not as standardized as in the other omics approaches. In this review, we synthesized the different steps that need to be carried out to obtain biological insight from annotated metabolite abundance raw data. These steps were grouped into three different modules: preprocessing, statistical analysis, and metabolic pathway enrichment. We included within each one of them the different state-of-the-art procedures and tools that can be used depending on the characteristics of the study, providing details about each method’s characteristics and the issues the reader might encounter. Finally, we introduce genome-scale metabolic modeling as a tool for obtaining pseudo-metabolomic data in situations where their acquisition is difficult, enabling the analysis of the resulting data with the modules of the described workflow. Full article

Arthritis, a global health burden comprising osteoarthritis and rheumatoid arthritis, demands advanced therapeutic approaches. In this context, flavonoids, a diverse group of naturally occurring compounds abundant in fruits, vegetables, and medicinal plants, have emerged as promising candidates for mitigating the inflammatory processes associated with arthritic conditions. This review aims, first, to provide a comprehensive exploration of the potential of flavonoids, focusing on specific compounds such as quercetin, epigallocatechin-3-gallate (EGCG), apigenin, luteolin, fisetin, silibinin, kaempferol, naringenin, and myricetin. The second section of this review delves into the anti-arthritic activities of these flavonoids, drawing insights from clinical trials and scientific studies. Each flavonoid is scrutinized individually to elucidate its mechanisms of action and therapeutic efficacy in the context of both osteoarthritis and rheumatoid arthritis. The third section of this review highlights the challenges associated with harnessing flavonoids for anti-inflammatory purposes. Bioavailability limitations pose a significant hurdle, prompting the exploration of innovative strategies such as the use of nanoparticles as delivery vehicles. In response to these challenges, the fourth section focuses on the emerging field of flavonoid-based nanoparticles. This includes detailed discussions on quercetin, EGCG, fisetin, and naringenin-based nanoparticles, highlighting formulation strategies and preclinical evidence supporting their potential in arthritis management. The targeted delivery to inflammatory sites and the exploration of synergistic combinations with other compounds are also discussed as promising avenues to enhance the therapeutic impact of flavonoids. This review consolidates current knowledge on flavonoids and their nanoformulations as potential therapeutic interventions for osteoarthritis and rheumatoid arthritis. By addressing challenges and presenting future research directions, this review aims to contribute to the advancement of innovative and effective strategies for alleviating the global burden of arthritis. Full article

An acidic extracellular pH value (pH_e) is characteristic of many cancers, in contrast to the physiologic pH_e found in most benign cells. This difference in pH offers a unique opportunity to design and engineer chemicals that can be employed for pH-selective reactions in the extracellular fluid of cancer cells. The viability of human skin melanoma and corresponding fibroblasts exposed to CaS dispersions is reported. The viability of melanoma cells decreases with CaS dispersion concentration and reaches 57% at 3%, a value easily distinguishable from melanoma control experiments. In contrast, the viability of benign fibroblasts remains nearly constant within experimental error over the range of dispersion concentrations studied. The CaS dispersions facilitate vinculin delocalization in the cytoplasmic fluid, a result consistent with improved focal adhesion kinase (FAK) regulation in melanoma cells. Thermodynamic considerations are consistent with the formation of H₂S from CaS in the presence of protons. The thermodynamic prediction is verified in independent experiments with solid CaS and acidic aqueous solutions. The amount of H₂S formed decreases with pH. An activation energy for the process of (30 ± 10) kJ/mol in the temperature range of 280 to 330 K is estimated from initial rate measurements as a function of temperature. The total Gibbs energy minimization approach was employed to establish the distribution of sulfides—including H₂S in the gas and aqueous phases—from the dissociation of CaS as a function of pH to mimic physiologically relevant pH values. Theoretical calculations suggest that partially protonated CaS in solution can be stable until the sulfur atom bonds to two hydrogen atoms, resulting in the formation of Ca²⁺ and H₂S, which can be solvated and/or released to the gas phase. Our results are consistent with a model in which CaS is dissociated in the extracellular fluid of melanoma cells selectively. The results are discussed in the context of the potential biomedical applications of CaS dispersions in cancer therapies. Full article

The incidence of male infertility has been increasing over the years and is now becoming a serious health problem. This trend has been followed by an increase in metabolic diseases, which are known to induce clear alterations in testicular metabolism, although the underlying mechanismremain unclear. Testicular metabolism displays several unique features, with testicular somatic cells being central in providing the conditions needed for spermatogenesis, including its nutritional and hormonal support. In addition to glucose and lactate, the two main energy sources used by the testis, glycogen is also present in testicular cells. Glycogen metabolism is a potential source of glucose to both testicular somatic (namely Sertoli and Leydig cells) and germ cells. Many of the enzymes involved in the pathways of the synthesis and degradation of glycogen were identified in these cells, emphasising the relevance of this complex carbohydrate. Glycogen, however, has other non-canonical functions in testicular cells; besides its role as a source of energy, it is also associated with events such as cellular differentiation and apoptosis. In this review, we address the relevance of testicular glycogen metabolism, focusing on its role in Sertoli and Leydig cells and spermatogenesis. In addition, all the available information on the role of glycogen and related pathways in male infertility cases is discussed. Our discussion highlights that glycogen metabolism has been somewhat overlooked in testis and its contribution to spermatogenesis may be underestimated. Full article

Sensing is an essential feature of life, where many systems have been developed. Diatomic molecules such as O₂, NO and CO exhibit an important role in life, which requires specialized sensors. Among the sensors discovered, heme-based gas sensors compose the largest group with at least eight different families. This large variety of proteins also exhibits many distinct ways of sensing diatomic molecules and promote a response for biological adaptation. Here, we briefly describe a story of two impressive systems of heme-based oxygen sensors, FixL from Rhizobium and DevS(DosS)/DosT from Mycobacterium tuberculosis. Beyond this, we also examined many applications that have emerged. These heme-based gas sensors have been manipulated to function as chemical and biochemical analytical systems to detect small molecules (O₂, CO, NO, CN⁻), fluorophores for imaging and bioanalysis, regulation of processes in synthetic biology and preparation of biocatalysts among others. These exciting features show the robustness of this field and multiple opportunities ahead besides the advances in the fundamental understanding of their molecular functioning. Full article

Polyoxometalates (POMs) are clusters of units of oxoanions of transition metals, such as Mo, W, V and Nb, that can be formed upon acidification of neutral solutions. Once formed, some POMs have shown to persist in solution, even in the neutral and basic pH range. These inorganic clusters, amenable of a variety of structures, have been studied in environmental, chemical, and industrial fields, having applications in catalysis and macromolecular crystallography, as well as applications in biomedicine, such as cancer, bacterial and viral infections, among others. Herein, we connect recent POMs environmental applications in the decomposition of emergent pollutants with POMs’ biomedical activities and effects against cancer, bacteria, and viruses. With recent insights in POMs being pure, organic/inorganic hybrid materials, POM-based ionic liquid crystals and POM-ILs, and their applications in emergent pollutants degradation, including microplastics, are referred. It is perceived that the majority of the POMs studies against cancer, bacteria, and viruses were performed in the last ten years. POMs’ biological effects include apoptosis, cell cycle arrest, interference with the ions transport system, inhibition of mRNA synthesis, cell morphology changes, formation of reaction oxygen species, inhibition of virus binding to the host cell, and interaction with virus protein cages, among others. We additionally refer to POMs’ interactions with various proteins, including P-type ATPases, aquoporins, cinases, phosphatases, among others. Finally, POMs’ stability and speciation at physiological conditions are addressed. Full article

The α-Gal epitope is an immunogen trisaccharide structure consisting of N-acetylglucosamine (GlcNAc)β1,4-galactose (Gal)α1,3-Gal. It is presented as part of complex-type glycans on glycoproteins or glycolipids on cell surfaces of non-primate mammalians. About 1% of all antibodies in human sera are specific toward α1,3-Gal and are therefore named as anti-α-Gal antibodies. This work comprises the purification and characterization of anti-α-Gal antibodies from human immunoglobulin G (IgG). A synthetically manufactured α Gal epitope affinity resin was used to enrich anti-α-Gal antibodies. Selectivity experiments with purified antibodies were carried out using enzyme-linked immunosorbent assays (ELISA), Western blotting, and erythrocyte agglutination. Furthermore, binding affinities toward α-Gal were determined by surface plasmon resonance (SPR) and the IgG distribution of anti α Gal antibodies (83% IgG2, 14% IgG1, 2% IgG3, 1% IgG4) was calculated applying ELISA and immunodiffusion. A range of isoelectric points from pH 6 to pH 8 was observed in 2D gel electrophoresis. Glycan profiling of anti α Gal antibodies revealed complex biantennary structures with high fucosylation grades (86%). Additionally, low amounts of bisecting GlcNAc (15%) and sialic acids (13%) were detected. The purification of anti-α-Gal antibodies from human IgG was successful, and their use as detection antibodies for α Gal-containing structures was evaluated. Full article