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Semen nano purification represents an innovative advancement in livestock reproductive biotechnology, offering a targeted, non-invasive approach to sperm selection. Traditional semen processing techniques, such as centrifugation, swim-up, and density gradient methods, primarily rely on physical characteristics like motility and morphology, which often fail to eliminate apoptotic, acrosome damaged or functionally impaired spermatozoa. In contrast, magnetic nano-purification enables selective removal of defective sperm based on molecular surface markers, including phosphatidylserine, ubiquitin, acrosomal glycans and other membrane proteins associated with specific conditions. This review explores how understanding sperm subpopulation diversity and surface biomarker expression provides a foundation for advanced, fertility-driven sperm selection strategies. It further discusses the principles of magnetic nanoparticle synthesis, surface functionalization, and the practical workflow of semen purification. Comparative studies demonstrate that nano-purified spermatozoa exhibit superior membrane integrity, motility, mitochondrial activity, and DNA quality while reducing oxidative stress. Notably, field trials have shown enhanced conception rates with nano-purified semen at half the conventional sperm dose. The method's low cost, safety, and ease of use in field settings make it a practical option for its utility in artificial breeding programs. Future perspectives highlight its potential for multiplexed selection and non-invasive sex-sorting through sperm surface biomarker-specific conjugation. Collectively, magnetic nano purification stands as a transformative strategy to improve sperm quality, enhance reproductive outcomes, and support genetic advancement in livestock production systems.

The field of nanoparticle-based biotechnology has undergone substantial advancement, characterized by progress in targeted drug delivery systems, the development of innovative diagnostic and imaging platforms, the expanded adoption of environmentally sustainable ("green") synthesis approaches, and an increasing emphasis on the integration of emerging technologies such as artificial intelligence and nanorobotics. Conventional nanoparticle synthesis often involves toxic reducing agents; however, recent advances promote eco-friendly green synthesis methods utilizing biological systems such as bacteria, fungi, algae, yeast, plants, and actinomycetes. These biological approaches are safe, sustainable, cost-effective, and capable of producing highly stable Nanoparticles (NPs). The interaction of nanomaterials with biological systems is crucial for developing intracellular and subcellular drug delivery technologies with minimal toxicity, governed by nano-bio interface mechanisms such as cellular translocation, surface wrapping, embedding, and internal attachment. Key factors influencing NP behavior include morphology, size, surface area, surface charge, and ligand chemistry. Magnetic nanoparticles, particularly iron-based forms, exhibit unique superparamagnetic properties that are strongly influenced by particle size, as explained by the Néel relaxation mechanism, in which thermal energy induces flipping of magnetic moments. Nanoparticles demonstrate diverse modes of action, including antimicrobial activity, reactive oxygen species (ROS)-induced cytotoxicity, genotoxicity, and plant growth promotion. NP performance and biological effects are strongly dependent on their size, shape, dosage, and concentration. This critical review article aims to elucidate evolution, classification, preparation methods, and multifaceted applications of nanoparticles.

The application of nanotechnology in gastroenterology represents a significant shift toward more precise, effective, and less invasive management of gastrointestinal (GI) diseases. By engineering materials at the nanoscale, researchers have developed sophisticated systems capable of overcoming formidable biological barriers, enabling targeted drug delivery, and providing unprecedented insights into disease pathophysiology through advanced diagnostic imaging and sensing. This review provides a comprehensive analysis of nanoparticle-based approaches for the diagnosis and treatment of major GI conditions, including inflammatory bowel disease (IBD), Helicobacter pylori infection, colorectal cancer (CRC), and gastric ulcers. It synthesizes recent progress, critically evaluates persistent challenges related to manufacturing and safety, and explores the future directions essential for translating promising laboratory discoveries into routine clinical practice. The field is characterized by a dynamic interplay between rapid scientific innovation and the equally critical need to solve complex problems of scalability, standardization, and regulatory compliance.

Triple negative breast cancer (TNBC) is a biologically heterogeneous disease that is treated according to stage at diagnosis. Early steps toward treatment personalization used staging for prognostication and later incorporated residual disease burden after neoadjuvant therapy to guide adjuvant treatment decisions. Therapeutic advances, particularly with immunotherapy and poly (ADP-ribose) polymerase inhibitors, have progressed more rapidly than the ability of clinical trials to adapt accordingly, leaving many critical questions regarding treatment combinations and sequencing unanswered. Adapting neoadjuvant and adjuvant strategies according to dynamic changes in the tumor, tumor microenvironment (TME) and novel biomarkers dynamics offers a compelling framework for both treatments escalation and de-escalatation. This review traces the historical evolution of TNBC treatment, examines the challenges of tumor heterogeneity and residual disease after neoadjuvant therapy, and explores the prognostic impact of the TME. We then appraise the latest evidence on poly (ADP-ribose) polymerase inhibitors, antibody-drug conjugates, and immunotherapy in the early setting, outlining a path toward more individualized therapeutic approaches.

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The global aging population has led to age-related digestive dysfunction, which has become a key driver of malnutrition and declining health. Physiological degeneration in older adults severely reduces nutrient bioavailability, making conventional single nutrient supplementation ineffective. Nutrient delivery systems tailored to the physiological constraints of the elderly show great value in alleviating geriatric malnutrition. Micro/nanoencapsulation, emulsions, and gels are particularly promising platforms for elderly-targeted food innovation due to their tunable structure, controlled targeted release, and good biocompatibility. Moreover, combining delivery systems with 3D printing for personalized nutrition and dysphagia-friendly texture design has emerged as an important trend in age-appropriate food development. This review outlines the digestive physiological constraints of the elderly and the design principles of nutrient delivery systems, highlights the adaptive optimization and recent applications of major delivery technologies in geriatric foods, and discusses intervention strategies, current challenges, and future directions. It aims to provide theoretical support for the research and innovation of functional foods tailored for older adults.

Accurate prediction of protein function is fundamental to progress in biotechnology and biomedicine, yet progress remains severely hampered by the widening chasm between exponentially growing genomic data and the limited capacity for functional annotation. High-throughput sequencing and metagenomics have driven an explosion in sequence data that far outstrips experimental characterization. UniProt now contains over 203 million protein entries, of which only ~2% have been experimentally validated. This widening "sequence-function gap" exceeds the reach of traditional homology-based tools such as BLAST (v2.17.0) and HMMER (v3.2), which are inherently constrained by sequence identity thresholds. The emergence of Protein Language Models (PLMs), including ESM and ProtTrans, has introduced a transformative paradigm, thereby shifting functional inference from similarity-based retrieval to geometric reasoning within learned semantic spaces. Nevertheless, current approaches remain largely confined to unimodal or narrowly bimodal frameworks, failing to capture the inherently multidimensional determinants of enzymatic function, including active-site geometry, chemical reaction logic, and literature-embedded semantic context. This review systematically adopts a multimodal global-fusion perspective, elucidating how three-dimensional geometric features, chemical reaction semantics, and textual knowledge graphs are synergistically integrated around PLMs as a core backbone. We delineate complementary mechanisms and integration strategies that together enable fine-grained protein function annotation beyond the performance ceiling of single-sequence methods. Furthermore, we survey the translational potential of such frameworks from computational prediction to real biological applications, and critically examine persistent bottlenecks including activity cliffs, transition-state inference, and conformational dynamics. We identify the integration of physics-informed machine learning with dynamics-aware architectures as a pivotal direction toward a causal, mechanism-level understanding of protein function.

Biogas is a key renewable energy vector that can support the transition toward a net-zero carbon economy. Its direct use as a natural gas substitute is limited because it must be upgraded to meet CH4 purity specifications required for injection into the gas grid or for use as a vehicle fuel. This review summarizes current progress in photosynthetic biogas upgrading, an emerging biotechnology based on the symbiotic action of microalgal-bacterial consortia capable of supporting gas purification with nutrient recovery in a single integrated process. This biotechnology relies on two stages: an absorption unit that enables gas-liquid mass transfer of the biogas pollutants, and a photobioreactor in which CO2 and other contaminants are removed. Optimal system performance is strongly influenced by the liquid to gas (L/G) ratio, with values between 0.5 and 1.0, typically balancing effective CO2 removal and limited CH4 dilution. High-alkalinity nutrient media (1.5-2.5 gIC L-1) and pH > 9 remain essential to sustain the chemical gradients driving CO2 mass transfer. Robust microalgae/cyanobacteria such as Chlorella vulgaris and Pseudanabaena sp. frequently dominate these systems. Recent efforts in the biostimulation of photosynthesis are presented based on their potential to enhance biomass productivity and CO2 removal, which could decrease the footprint of the process and facilitate its large-scale adoption for biomethane production.

Solid-state fermentation (SSF) is a pivotal biotechnology in the circular economy, leveraging agri-food industrial waste and byproducts to produce high-value bioproducts while minimizing organic waste. By aligning with sustainability goals and zero-waste principles, SSF enables the production of enzymes, bioactive compounds, and secondary metabolites for food, agriculture, and biomedical applications. Recent advancements have optimized critical parameters, including substrate selection, culture conditions, and scalable bioreactor designs, enhancing process efficiency and reducing environmental impact. Despite progress, challenges persist in maximizing production yields and fostering industrial adoption. Addressing these hurdles, particularly through integrated environmental and techno-economic analyses, is essential to solidify SSF's role as a sustainable and competitive bioprocessing method. This review analyzes the latest advances in SSF, including the valorization of food and agro-industrial wastes, innovative bioreactor designs, microbial engineering for more efficient strains, bioenergy production and its integration into biorefineries, and contributions to the circular bioeconomy. Thus, SSF emerges as a key technology in sustainable industrial biotechnology, offering eco-friendly alternatives and promoting a more efficient production model.

Centers of Excellence (CoEs) are key instruments for advancing scientific excellence, innovation, and socio-economic development in Europe. The paper compares three leading European Centers of Excellence in plant science: the Max Planck Institute of Molecular Plant Physiology (Potsdam-Golm, Germany), the Center for Plant Systems Biology at the Flanders Institute of Biotechnology (Gent, Belgium), and the Center of Plant Systems Biology and Biotechnology (Plovdiv, Bulgaria). The survey explores their organizational structures, funding sources, scientific focus and impact on the regional socio-economic environment. All centers impose substantial influence on the scientific advancement of their countries. The study indicates that the contributions of these institutions extend beyond national borders, supporting scientific progress at the European and global level. In addition to research impact and innovation potential, these institutions enable socio-economic development of their regions by improving local infrastructure, creating jobs, promoting a favorable business environment, and facilitating stronger linkages between academia and industry.

Plant metabolism is essential for coordinating growth, development, and defense under changing environmental conditions. Plants continuously adjust their metabolic pathways to balance resource allocation between growth and immune responses. Under stress, metabolic reprogramming redirects energy and resources toward the production of defense compounds and activation of immune signaling pathways. These changes involve complex interactions among primary metabolism, specialised metabolites, and regulatory networks, including calcium signaling, reactive oxygen species, and phytohormones. Advances in metabolomics and multi-omics technologies have improved understanding of the metabolic control of plant immunity; however, knowledge remains fragmented, and an integrated framework linking metabolism, development, and defense is still emerging. This review examines plant immunometabolism by highlighting the dynamic relationships between metabolic networks and immune functions during development and stress. It discusses pathways that influence growth, stress-induced metabolic shifts linked to defense, and how signaling interacts with metabolism. Progress in metabolomics, transcriptomics, proteomics, and computational modeling that supports systems-level analysis of plant metabolism is also summarized. In addition, potential applications in agriculture and biotechnology, including metabolic engineering, genome editing, and metabolomics-based breeding, are considered in relation to crop resilience. By integrating metabolism, signaling, and systems biology, this review provides a broad perspective on how metabolic reprogramming shapes the growth-defense trade-off in plants and outlines future directions for developing climate-resilient crops.

Hepatic fibrosis is a progressive pathological condition characterized by chronic inflammation and excessive extracellular matrix deposition (ECM), which may progress to cirrhosis and liver failure. Although specialized pro-resolving lipid mediators have emerged as potential therapeutic agents, their role in advanced hepatic fibrosis remains incompletely defined. This study aimed to determine whether Maresin 1 (MaR1), an endogenous pro-resolving lipid mediator, promotes the resolution of hepatic fibrosis and modulates the associated inflammatory response. Hepatic fibrosis was induced in mice and rats using diethylnitrosamine (DEN). Animals were subsequently treated with MaR1 or vehicle. Histological and biochemical parameters, apoptosis and proliferation markers, and immune profiles associated with hepatic macrophages polarization were assessed. Additionally, the expression and subcellular localization of retinoic acid related orphan receptor alpha (RORα) and nuclear factor kappa B (NF-κB p65) were analysed. MaR1 treatment significantly attenuated hepatic fibrosis, reduced the ECM accumulation, and promoted restoration of liver parenchyma, accompanied by decreased hepatocellular injury and enhanced regenerative capacity. MaR1 also induced immune reprogramming, favouring anti-inflammatory and homeostatic macrophage phenotypes. These effects were associated with increased nuclear activation of RORα and modulation of NF-κB signalling pathways. These findings demonstrate that MaR1 promotes the resolution of hepatic fibrosis through macrophage polarization and modulation of the RORα/NF-κB axis. This study advances the understanding of pro-resolving mechanisms in hepatic fibrosis and positions MaR1 as a pharmacologically relevant candidate for the development of targeted antifibrotic therapies in chronic liver disease.

Mycoplasma and Ureaplasma species are understudied opportunistic pathogens that infect humans, animals and plants. These infections are often asymptomatic, which, together with fastidious growth requirements, makes them challenging to detect. The review aimed to provide a bibliometric analysis of available literature to reflect and assess trends, progress and knowledge gaps in this field. This article is a literature review. A bibliometric analysis of 19 486 documents from 1992 to 2022 was conducted using the Web of Science database and in-depth analyses on RStudio. China and the United States produced a high number of publications and citations. South Africa, the first most-cited African country, contributed 685 publications, ranking 24th globally with 2031 citations. Veterinary Microbiology was the highest performing journal with 448 papers and 10 036 citations. The most frequent keywords were 'infection' and 'Ureaplasma urealyticum'. Research on Mycoplasma and Ureaplasma infections has progressed over time, but mainly in developed countries. The restricted publications and moderate citations in South Africa suggest research gaps in understanding the true burden and impacts of these infections. This study provides a comprehensive bibliometric overview of Mycoplasma and Ureaplasma infections and reports the global and local progress in this field. The overall moderate, steady growth highlights the need for broader international collaboration and expanded research efforts in low-resource countries to address existing research gaps. This expansion is essential, particularly in clinical research, for strengthening both surveillance and treatment guidelines.

Advancements in synthetic biology (SynBio) and other emerging and converging technologies, such as artificial intelligence (AI) additive manufacturing (3D printing), and nanotechnology are driving progress at an unprecedented pace. However, these promising and groundbreaking advances could also lead to novel biological risks, including the potential development of SynBio-enabled bioweapons (BW). Conducting a Delphi process, we consulted 13 experts from diverse relevant sectors. The multi-stage process included insights from literature reviews, expert interviews, two rounds of expert surveys, and two workshops. We identified consistent biological threat prioritizations and established consensus-driven policy recommendations. Based on this, we developed a novel hybrid governance framework. Our key proposal includes a multifaceted and integrative approach involving four sequential, iterative components: raising awareness; establishing robust training and monitoring systems to improve biosecurity measures; developing and implementing agile governance frameworks; and strengthening international treaties, such as the Biological Weapons Convention (BWC). We consider these integral, interconnected components to be interdependent and equally important. In an era of SynBio, AI-driven bioengineering, and democratization of biotechnology, implementing these recommendations will better safeguard against the potential misuse of these advancements in the context of the development and proliferation of BW.

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal and aggressive tumor types, with a dismal 5-year survival rate of less than 15%. Despite major advances in understanding PDAC biology, therapeutic progress has been limited. Numerous preclinical studies have provided encouraging evidence that immune-based therapies may be effective. However, the clinical translation of immunotherapies for PDAC treatment has proven difficult with a lack of favorable tumor responses outside of a very select group of patients such as patients with MSI high tumors. Immune checkpoint inhibitors, as well as combination strategies with targeted radiotherapy or chemotherapy, have largely failed to demonstrate meaningful survival benefits for the majority of PDAC patients. Increasing evidence indicates that PDAC harbors a uniquely complex and multifaceted immunosuppressive microenvironment, which plays a central role in shielding malignant cells from effective antitumor immunity. Overcoming this barrier requires the development of rational and effective combination regimens that simultaneously target both the tumor and its surrounding immune microenvironment. Novel strategies, including the use of natural killer cell-based therapies, reprogramming of cancer-associated fibroblasts, and integration of predictive or prognostic biomarkers, hold promise for enhancing therapeutic efficacy. This review summarizes recent progress in PDAC immunotherapy, highlights key challenges, and discusses emerging approaches designed to improve patient outcomes.

Fluorescent sensors have emerged as indispensable tools for detecting various fields, including visualising biological processes in molecular biology, clinical diagnostics, biotechnology, and environmental monitoring, due to their high sensitivity, selectivity, excellent biocompatibility, ease of use, and low cost. However, conventional fluorophores, which exhibit diminished fluorescence upon aggregation/detection, that is, in the aggregated state, predominantly suffer from aggregation-caused quenching (ACQ); thus, limit their potential in sensing technologies. To overcome, the new aggregation-induced emission (AIE)-luminogens have been extensively applied in biomedical imaging, optoelectronics, stimuli-responsive systems, drug delivery, and chemical sensing, as AIEgens display greater fluorescence upon aggregation, offering a powerful solution. This review provides a comprehensive, systematic overview of the latest advancements in organic AIE-based fluorescent luminogens. It begins with the fundamentals of AIE and their use in ion sensing, followed by a discussion of the detection of explosives and bioactive molecules. We then summarized by highlighting the diverse range of approaches to establishing an association between the structures of AIEgens and their sensing performance, and finally discussed the current challenges and future opportunities in this rapidly growing research area. We hope this review will spark new ideas and inspire new endeavors in this emerging research area, thereby further promoting state-of-the-art progress in sensing.

Background:The enhancement of the therapeutic window (TW) in oncology remains a significant challenge, as the majority of anticancer treatments face difficulties in achieving optimal tumor control while minimizing adverse effects. Traditional chemotherapeutic agents, while demonstrating efficacy, are constrained by their limited TWs and the occurrence of systemic adverse effects.Objective: Recent advancements in precision medicine have revolutionized this paradigm by facilitating targeted tumor intervention via molecularly guided therapies, immuno-oncology strategies, and biomarker-driven patient classification. Novel approaches, including nanomedicine, antibody-drug conjugates, and prodrug formulations, improve therapeutic selectivity through the optimization of drug delivery, biodistribution, and release kinetics.Methodology: The concurrent advancements in radiotherapy, adaptive dosing methodologies, and toxicity assessment instruments have expanded the potential to enhance treatment intensity while preserving the integrity of normal tissues. In the future, the convergence of artificial intelligence (AI), multiomics profiling, and systems biology is anticipated to enhance therapeutic decision-making and expedite the creation of more personalized and adaptive interventions.Results:The efficacy of cancer treatments is substantially limited by notable shortcomings in research, despite progress in precision oncology. Tumor heterogeneity, the emergence of resistance mechanisms, and the absence of reliable biomarkers for anticipating treatment outcomes present significant impediments. The utilization of multiomics data and AI in clinical decision-making remains in its early stages, constrained by limitations in data validation and standardization. Furthermore, the translation of transdisciplinary concepts into accessible treatments is crucial, especially in environments with limited resources. Consequently, addressing these multifaceted issues is essential for improving the efficacy and safety of cancer treatments.Conclusion:This review integrates contemporary strategies and examines prospective pathways for expanding the TW, highlighting the intersection of technology, biology, and clinical innovation in the progression of cancer treatment.

Cancer immunotherapy has transformed oncology by harnessing the immune system to recognize and eliminate malignant cells. However, currently available options, including immune checkpoint inhibitors and cellular therapies, remain limited due to immune-related toxicities, high costs, off-target effects, and variable patient responses. These challenges highlight the need for alternative, synthetic immune-modulating strategies with improved precision, safety, and scalability. Aptamers have recently emerged as promising synthetic immune modulators. Owing to their chemical synthesis, small size, low immunogenicity, and extensive chemical tunability, aptamers offer distinct advantages over protein-based biologics, including enhanced tissue penetration, batch-to-batch consistency, and flexible pharmacokinetic optimization. Beyond their established diagnostic applications, aptamers are being applied as therapeutic agents capable of modulating immune checkpoints, cytokine signaling, and immune cell recruitment within the tumor microenvironment. Aptamer-drug conjugates (ApDCs) also represent a powerful extension of this technology, enabling targeted delivery of cytotoxic or immunostimulatory payloads to tumors while minimizing systemic toxicity. Through this review, we aim to provide a comprehensive overview of aptamer-based immunotherapies, encompassing molecular engineering strategies, SELEX optimization, and structural design principles that underpin target specificity and functional activity. We further examine preclinical and emerging clinical progress, translational challenges related to formulation, pharmacokinetics, and regulatory considerations, and the evolving role of ApDCs in cancer treatment. Finally, we discuss future perspectives for aptamer technologies as next-generation synthetic immune modulators, with the potential to complement or surpass conventional immunotherapeutic approaches in precision oncology.

Tuberculosis (TB) remains a major global health problem, and treatment progress is increasingly threatened by rising multidrug-resistant tuberculosis (MDR-TB). Delamanid (DLM), a nitroimidazole drug, has shown good efficacy and safety against both drug-susceptible and drug-resistant Mycobacterium tuberculosis (Mtb) strains. However, data on its resistance mechanisms, drug susceptibility testing (DST), clinical effectiveness, safety, and pharmacokinetics remain limited. This review aims to summarize the most recent molecular, structural, and clinical evidence related to DLM. A comprehensive literature search was performed using WHO publications and major scientific databases, including PubMed, Web of Science, Embase, Scopus, and the Cochrane Library. Studies published through 2024 and early 2025 on DLM resistance, mechanisms of action, DST, pharmacokinetics, safety, and treatment outcomes were included. Structural analyses of key proteins involved in DLM activation were carried out using crystal structures and AlphaFold models. Recent research identified multiple mutations in the F420-dependent activation pathway, particularly in ddn, fgd1, fbiA, fbiB, fbiC, and fbiD that contribute to DLM resistance. Structural modeling demonstrated how these mutations affect protein stability and cofactor binding. Clinical studies showed that DLM-containing regimens improve culture conversion and treatment success, especially when combined with oral agents such as bedaquiline and linezolid. Safety data indicate that DLM is generally well tolerated, with QT prolongation being the main but manageable adverse effect. DLM is an important and effective component of MDR-/XDR-TB treatment. A clearer understanding of its resistance mechanisms, pharmacological properties, and clinical outcomes can support better regimen design and help prevent the development of further resistance.