Search Results (19,823)

Phytoplankton are primary producers in the aquatic ecosystems whose pigments, cell size, and physiological state affect how they absorb light and fix carbon. The phytoplankton absorption coefficient (ɑ_ph(λ)) in the visible spectrum is a fundamental cellular optical property that determines phytoplankton–light interactions in the marine environment. This property links biological processes to ocean color remote sensing reflectance (Rrs), enabling an assessment of environmental and biogeochemical conditions in the ocean using ocean color satellites. This study presents a multi-stage systematic review of six decades (1965–2025) of ɑ_ph(λ) research, with a focused synthesis of developments in the past decade. A bibliometric analysis empirically examines the research growth of the field and its thematic convergence into methodological divergence across six decades. Cluster analysis was used to compile influential research topics as well as emerging trends, to determine the scope and design of the systematic review. A focused systematic review of studies in the past decade (2015–2025) has been carried out to identify conceptual and theoretical advances, major observational and algorithmic improvements, and ongoing challenges. The data analyses highlight the accuracy achieved by various studies, the complexity of applications of algorithms, and product-focused developments. The ongoing challenges identified include resolving optical degeneracy, vertical structure acquisition, and scaling methods for operational use. This review concludes the centrality of ɑ_ph(λ) as a key parameter to next-generation ocean color science, biogeochemical modeling, and climate-related ecosystem monitoring. Full article

This review highlights the recent advances in the synthesis of 1,4-diazatriphenylenes and their various structural analogs. It focuses on several methodologies, including condensation reactions and intramolecular cyclizations of 2,3-di(het)aryl-substituted pyrazine derivatives. These methods exploit either oxidative photocyclization (the Mallory reaction), intramolecular cyclodehydrogenation (the Scholl reaction), or intramolecular S_N^H reactions (nucleophilic aromatic substitution of hydrogen) involving 2-bis(het)aryl-substituted 1,4-diazine derivatives. Additionally, the review explores the potential applications of these compounds as fluorescent and/or semiconducting materials in organic electronics, as well as their role in coordination chemistry and biological issues. It summarizes the literature from 2018 to March 2026, complementing the data discussed in our previous review. Full article

The increasing prevalence of antimicrobial resistance (AMR) has promoted the development of advanced biomaterials capable of overcoming the limitations of conventional antibiotics. In this context, metal nanoparticle hybrid hydrogels (MNHHs) have emerged as multifunctional platforms that integrate the high water-retention capacity and biocompatibility of hydrogels with the antimicrobial properties of metallic nanoparticles (MNPs). This review critically analyzes recent advances in the design, physicochemical properties, antimicrobial mechanisms, and biomedical applications of these systems. Current evidence demonstrates that MNHHs can achieve antimicrobial efficiencies above 98–99%, with minimum inhibitory concentrations as low as 0.78 µg mL⁻¹ and inhibition zones of up to 25 mm against clinically relevant pathogens. Furthermore, the incorporation of MNPs significantly improves the mechanical properties of hydrogels and enables controlled and sustained metal ion release for periods of up to 14 days. Despite these promising results, important challenges remain regarding cytotoxicity, release control, the lack of experimental standardization, and the limited understanding of long-term biological effects. Overall, MNHHs represent a promising strategy for infection control, regenerative medicine, and controlled drug delivery; however, their clinical translation still requires the development of reproducible, safe, scalable, and highly biocompatible systems. Full article

Bitter phytochemicals, including alkaloids, terpenoids, and bitter glycosides, are abundant in medicinal food plants and exhibit well-documented anti-inflammatory, hypoglycemic, and other bioactivities relevant to human health. However, the inherent bitterness of these compounds presents a significant sensory barrier to patient compliance and limits their application as functional food ingredients. This review provides a comprehensive and interdisciplinary synthesis of current knowledge on bitter compounds in medicinal food plants, integrating perspectives from phytochemistry, molecular pharmacology, and sensory science. We summarize the major chemical classes of bitter phytochemicals, critically evaluate methods for their isolation and identification—from classical sensory-guided fractionation to modern computational approaches such as molecular docking and metabolomics—and analyze three principal strategies for bitterness regulation: physical removal, biological transformation, and sensory modulation (including molecular inclusion and TAS2R receptor blocking). We also briefly touch upon the extraoral expression of TAS2Rs and there suggested links to local immune responses and metabolic regulation, noting that this may be relevant to the concept of “taste–bioactivity homology.” The review further highlights ongoing challenges, such as the identification of unknown bitter compounds and the lack of standardized sensory evaluation systems, and outlines possible directions for improving bitterness analysis and regulation in medicinal food plants. Full article

At present, treated wastewater may still contain residual nutrients and micropollutants, including heavy metals, pharmaceuticals, and dyes, which can negatively affect receiving water bodies. Increasingly stringent environmental regulations, including Directive (EU) 2024/3019, require both enhanced removal of these contaminants and greater integration of renewable energy sources in wastewater treatment plants. This paper presents a review of biomass-based wastewater polishing technologies employing biological agents such as microalgae, fungi, bacteria, co-cultures and duckweed for the removal of residual contaminants from treated effluents. The compiled data indicate that while optimal conditions can drive pollutant removal efficiencies beyond 90%, system performance varies widely depending on species selection, wastewater characteristics, and operational conditions (e.g., pH, temperature, salinity, nutrient availability, and light intensity). In addition to effluent polishing, the produced biomass can be valorized for bioenergy generation, contributing to renewable energy production and supporting circular economy principles in wastewater treatment plants. Despite these benefits, biomass harvesting remains a major technical and economic bottleneck, often representing a significant share of operational costs and limiting large-scale implementation. Overall, biomass-based treatment technologies are a promising approach for improving effluent quality and supporting renewable energy objectives; however, further advances in biomass recovery are required for broader application. Full article

Artificial intelligence (AI) is increasingly influencing nanopharmaceutical development by supporting the transition from empirical formulation screening toward predictive, data-driven, and translationally oriented design. Nanocarrier-based therapeutics are governed by nonlinear relationships among material composition, physicochemical attributes, manufacturing parameters, biological identity, pharmacokinetics, toxicity, and therapeutic performance. In this review, we examine how AI can contribute to nanopharmaceutical development from predictive formulation design to clinical translation. We synthesize current applications of machine learning, deep learning, physics-informed modeling, hybrid mechanistic–AI approaches, and automated optimization workflows, with emphasis on critical quality attribute modeling, multi-objective optimization, design of experiments, quality-by-design, process analytical technology, digital twins, and continuous manufacturing. We also discuss applications involving nano–bio interactions, pharmacokinetics, toxicity, immunogenicity, and precision nanomedicine. AI-based approaches can support rational nanocarrier design, identify nonlinear formulation–property relationships, guide optimization, improve process understanding, and integrate heterogeneous experimental, biological, and manufacturing datasets across diverse nanopharmaceutical platforms. These methods are particularly relevant for modeling protein corona formation, cellular uptake, intracellular trafficking, biodistribution, pharmacokinetics, toxicity, immunogenicity, and patient-specific responses. However, translational implementation remains limited by fragmented datasets, inconsistent reporting standards, limited interpretability, insufficient external validation, uncertain predictions, poorly defined applicability domains, and evolving regulatory expectations for adaptive computational models. Overall, AI should be viewed not only as an optimization tool, but also as a translational framework connecting formulation science, biological prediction, manufacturing control, and clinical implementation. Future progress will depend on standardized data infrastructures, explainable and externally validated models, uncertainty quantification, applicability-domain definition, hybrid mechanistic–AI frameworks, regulatory-ready documentation, and clinically relevant case studies. Full article

To understand glycan–protein interactions at biological interfaces, designing surfaces modified with structurally controlled glycans is highly important. In particular, naturally occurring glycosaminoglycans (GAGs) possess periodic sugar arrangements that play important roles in protein recognition, highlighting the need for the development of periodic glycopolymer model systems that can serve as GAG mimics for quantitative interaction analysis. In this study, sequence-controlled periodic glycopolymers were synthesized by reversible addition–fragmentation chain-transfer (RAFT) polymerization and immobilized onto gold surfaces to construct glycan-modified interfaces. The synthesized material was a terminally functionalized periodic glycopolymer with the most basic structure, consisting of alternating maltose-containing vinyl ether (MalVE) units and ethyl maleimide (EtMI) units, with a trithiocarbonate group at the ω-terminal. This trithiocarbonate group was converted to a thiol group for immobilization through Au–S bond formation. Structural characterization by ¹H NMR spectroscopy, size exclusion chromatography (SEC), MALDI-TOF mass spectrometry, and UV–vis spectroscopy confirmed the structure as designed. Quartz crystal microbalance (QCM) measurements verified the stable immobilization of thiol-terminated periodic glycopolymers on the gold surface, and allowed for estimation of graft density and quantitative analysis of glycan-protein interactions at the modified interface. The periodic glycopolymer-modified surfaces exhibited selective binding behavior toward concanavalin A (ConA) compared to bovine serum albumin (BSA), with apparent binding constants on the order of 10⁶–10⁷ L mol⁻¹. This enhanced binding behavior indicated that specific and multivalent interactions with proteins also occurred at periodic pendant maltose residues along the main chain. These results demonstrate that the gold surface modified with end-functional periodic glycopolymers synthesized by RAFT polymerization provides a versatile platform for quantitative analysis of glycan-protein interactions and suggests potential applications for periodic glycopolymers as functional materials. Full article

Biomass valorization plays a vital role in achieving carbon neutrality and circular economy frameworks. Owing to its carbon-rich structure, biomass represents a promising feedstock to produce bio-based hydrocarbons via biological and thermochemical pathways. While biological conversion routes have been extensively studied, their deployment at commercial scale is constrained by high capital costs and low product yields. In contrast, thermochemical conversion technologies are increasingly being explored as viable large-scale biomass valorization routes. This review presents a comprehensive assessment of thermochemical pathways, with particular emphasis on hydrothermal liquefaction (HTL). The review identifies hydrothermal liquefaction (HTL) as a strategically advantageous route for wet and heterogeneous biomass valorization, due to simultaneous yields of liquid biocrude, and solid hydrochar. The review emphasizes the application of biocrude upgradation processes like hydrodeoxygenation under biphasic solvent systems using sulfided NiMo and CoMo catalysts. Further, the review also establishes hydrochar as a tunable functional material rather than a mere byproduct for applications in fields of energy production, soil amendment, and heterogeneous catalysis. The review article examines technology readiness levels of different biomass valorization techniques, and suggests that while combustion, anaerobic digestion, torrefaction, and transesterification are commercially mature, HTL and carbon capture utilization and storage (CCUS)-integrated fuel synthesis pathways remain at intermediate readiness. Additionally, the review carries out an in-depth study on artificial intelligence and machine learning (AI and ML) applications in biomass valorization, where it observes that Tree-based ensemble models, particularly Random Forest and XGBoost, show strong performance for several HTL prediction tasks, while Gaussian Process Regression and neural network–Bayesian optimization approaches provide additional advantages for uncertainty estimation and process-level optimization. Finally, the future research opportunities in biomass valorization and AI/ML application in HTL-process optimization have been identified for improving the bio-based fuel production techniques. Full article

Salmonella remains one of the most critical zoonotic pathogens in the poultry sector, linked to animal disease, foodborne illness, and the global crisis of antimicrobial resistance (AMR). Poultry acts as a major reservoir, enabling Salmonella transmission from hatchery to retail products through horizontal, vertical, and environmental routes. Despite the use of biosecurity, vaccination, antibiotics, and chemical decontamination, effective and sustainable control across the poultry value chain remains difficult, particularly in the face of rising multidrug-resistant strains and growing consumer concerns over chemical residues. Bacteriophages (phages), viruses that selectively infect and lyse bacteria, have emerged as a promising biological alternative for Salmonella control. Although many studies have reported the effectiveness of phages against bacterial species, including Salmonella, in the poultry industry, reports on their full potential to combat antimicrobial-resistant Salmonella across the entire poultry value chain remain limited. Therefore, this review synthesizes current evidence on the application of phages throughout the poultry value chain, including on-farm interventions, processing plant decontamination, and food packaging and storage. Findings from the reviewed articles indicate over a 90% reduction in Salmonella spp. in poultry farms and post-harvest meat, along with lower mortality in phage-treated groups compared to untreated groups; however, these outcomes depend on several factors (e.g., phage strains, concentrations, application methods, and environmental conditions). Laboratory, pilot, and field studies consistently demonstrate that phage preparations, especially when formulated as cocktails or combined with complementary interventions, can achieve substantial reductions in Salmonella, including antibiotic-resistant serovars, in live birds, eggs, poultry environments, and meat products. Unlike antibiotics and chemical sanitizers, phages act with high specificity, preserving beneficial microbiota and maintaining the sensory and nutritional quality of poultry products. Their safety has been supported by toxicological and genomic assessments, and several phage-based products have obtained regulatory approval, including Generally Recognized as Safe (GRAS) status for food applications in the United States. By integrating efficacy, safety, regulatory, and practical deployment data, this review highlights bacteriophages as a scientifically validated and One Health–aligned tool capable of reducing Salmonella transmission from farm to fork across the poultry value chain, thereby laying the foundation for their future adoption in the poultry industry. Phage-based interventions offer a sustainable pathway to enhance food safety, limit antimicrobial resistance (AMR) dissemination, and strengthen consumer confidence in poultry products. However, the major limitation is the emergence of phage-resistant bacterial strains, as well as the potential involvement of some phages in the transfer of resistance and virulence genes, which could raise public concern. Nevertheless, the use of phage cocktails and whole-genome sequencing, involving tools such as ResFinder and virulence finder, can facilitate the selection of safe phages for application. Full article

Immunoglobulins exhibit important biological functions, including the neutralization of cytotoxins, enhancement of phagocytic activity, and activation of the complement system, which have driven their widespread application in both the food and pharmaceutical industries. Due to their low cost and short production cycles, microbial expression systems such as bacteria and yeast have been increasingly developed in recent years for immunoglobulin production. However, microbial systems face considerable challenges in ensuring proper protein folding, accurate chain assembly, and the soluble expression of full-length immunoglobulins. Recent optimization strategies have focused on host engineering (e.g., modulating secretion pathways and chaperone proteins), the coordinated regulation of expression elements (e.g., optimizing the light-to-heavy chain ratio), and regulation of fermentation processes. In addition to summarizing the above strategies, this review discusses the progress made in expressing both full-length immunoglobulins and antibody fragments across different microbial hosts, analyzes the advantages and limitations of each system, and explores potential future directions, aiming to provide a reference for the efficient heterologous expression of immunoglobulins. Full article

Introduction: Aquatic chemical pollution is among the most worrying threats to ecosystem health. There is an ever-increasing variety of pollutant substances detected across the source-to-sea continuum, causing loss of biodiversity and ecological disequilibrium. Achieving cleaner and healthier systems relies on carrying out sustained, cost-effective, diagnosis and aquatic effects monitoring, within the adaptive management cycle. The available methods are, however, cumbersome, which creates a clear need for innovative expeditious approaches for low-cost surveillance monitoring. In the last decade, Raman Spectroscopy (RS) has gained wide recognition for application to biological questions, for its ability to uncover the complexity of molecules and their interactions. Various fields, from pharmacology to disease diagnosis and prognosis, have suffered an innovation revolution through the application of RS. In this technique inelastic light scattering of a small part of photons of an incident electromagnetic monochromatic light beam (ranging from near-infrared to visible or ultraviolet) is caused by the molecular vibration of chemical bonds. This results in shifts in energy, which indicate discrete vibrational modes of polarisable molecules, providing qualitative and quantitative assessments of the chemical composition and molecular structure of the sample. The technique shows high sensitivity, no need for sample preparation and the possibility of use in non-invasive and label-free analysis. Objective: The aim of this work is to present and discuss evidence about the application of Raman Spectroscopy (RS) to environmental diagnosis and aquatic effect monitoring of pollution. Methodology: The technique was applied to different biological models, i.e., diatoms, zebrafish embryos and larvae and freshwater snails. Quality assessments with diatoms were tested in environmental monitoring, while assessments with other models were done upon exposure to metals and organic contaminants. Results and conclusions: The Raman spectra obtained from the samples analysed comprised bands detected within the 800 to 2000 cm⁻¹ wavenumber range. These were related to bond vibrations of carbohydrates, DNA phosphate groups, proteins or CH, NH and OH stretching in lipids and proteins. Data analysis using chemometric methods clearly distinguished pollutant exposure from control sites or treatments, pointing out the potential for surveyance monitoring. The next steps include the comparison with other sensitive methods (e.g., locomotion and avoidance behaviours, omics methods) to assess efficiency and bring further mechanistic understanding. Full article

Laurinterol, a halogenated sesquiterpene produced by red algae of the genus Laurencia, is one of the most characteristic compounds within the laurane and cyclolaurane families. This review compiles and examines current knowledge on laurinterol, integrating evidence on its occurrence, biosynthesis, biological activities, and structural features. Within a functional and ecological framework, laurinterol is proposed as an archetypal Smart Secondary Metabolite (SSM), a concept that reflects the convergence of structural singularity, high abundance within its biosynthetic context, broad biological activity, multi-target interactions, and ecological or chemotaxonomic relevance. This perspective highlights its role in adaptive processes within producing organisms and associated trophic networks. Laurinterol exhibits a broad bioactivity profile, including antimicrobial, antimycobacterial, cytotoxic, antiparasitic, enzyme inhibitory, antifouling, and insecticidal or repellent effects. Structure–activity relationship (SAR) studies remain limited and are mainly developed in specific models, particularly against Naegleria fowleri. The current intellectual property landscape related to laurinterol, including patent applications, granted patents, and technological development trends, is also examined. Overall, this review positions laurinterol as a structurally distinctive and functionally relevant marine metabolite within chemical ecology and marine natural products research. Full article

Lung cancer remains the leading cause of cancer-related mortality worldwide, largely due to late-stage diagnosis, biological heterogeneity, and persistent challenges in staging and treatment selection. This narrative review summarizes current and emerging applications of AI across lung cancer screening and early detection, imaging-based staging and prognostication, tissue and liquid biopsy-based tumor characterization, treatment planning, surgical and intraoperative guidance, and drug discovery. In imaging, deep learning models have demonstrated high performance in pulmonary nodule detection, risk stratification, and prediction of molecular alterations, while also showing promise in improving screening efficiency and reducing interpretive variability. In pathology and liquid biopsy domains, AI enables prediction of driver mutations, immunotherapy response, and survival outcomes directly from histopathology slides, circulating tumor DNA, and other blood-based biomarkers, facilitating minimally invasive precision oncology approaches. In treatment planning and delivery, AI systems are being developed to support clinical decision-making, surgical planning (through advanced image segmentation and delineation of operative anatomy), and intraoperative navigation through robotic and computer vision-enabled platforms. Despite these advances, significant barriers remain, including limited real-world validation, algorithmic biases, workflow integration issues, and unresolved ethical and legal concerns. Future progress will depend on the development of transparent, clinically validated, and generalizable AI systems that augment rather than replace the expertise of clinical providers and healthcare teams. Active engagement from pulmonologists, oncologists, radiologists, and thoracic surgeons will be essential in guiding safe implementation and ensuring that AI-driven innovations translate into meaningful improvements in patient outcomes. Full article

Globally, Trichogramma Westwood (Hymenoptera: Trichogrammatidae) is known as the most effective biological control agent due to its ability to parasitize insect pest eggs. However, identifying an appropriate host is vital for Trichogramma to prosper. Therefore, this study delves into the complex role of semiochemicals in shaping the host-seeking behavior of Trichogramma parasitoids, with a particular focus on their responses to both plant-derived and host-derived cues. The mechanism of semiochemical reception in Trichogramma wasps relies on a highly specialized, sensitive olfactory and gustatory system to locate host eggs and mates. Semiochemicals, which mediate ecological interactions, have been identified as pivotal in influencing the parasitic efficiency of Trichogramma species. Trichogramma’s host-seeking behavior is influenced not solely by ovipositional cues but also by the intrinsic physical attributes of Lepidopteran hosts, such as the scales on the wings and abdomen, which emit semiochemicals capable of eliciting positive chemotactic responses, thereby guiding parasitoids toward optimal sites for oviposition. Furthermore, the interplay between insect-derived and plant-derived chemical cues exhibits a synergistic effect, collectively enhancing the chemotactic attraction of Trichogramma, thereby fine-tuning its host-seeking behavior with greater precision and specificity. This study further underscores Trichogramma’s innate behavioral ability to discriminate between host eggs of varying developmental stages, facilitating the precise identification and selection of the most suitable host for parasitization. Age and experience both make Trichogramma more selective of hosts, but younger parasitoids may take a broader approach to host selection due to their greater life expectancy. Furthermore, the removal of these cues affects their host localization and learning abilities. Associative learning enables Trichogramma to exhibit flexible behaviors, providing them with a selective advantage; allows them to explore various hosts; and reduces environmental uncertainty. Plant structure, host density, and host age are the key factors that significantly influence the foraging and parasitism of Trichogramma. The searching speed of this parasitoid is significantly influenced by temperature. Heat stress increases VOC emissions in plants such as potato via stomatal opening, reducing herbivore attraction and enhancing parasitoid recruitment. Furthermore, air pollution, including CO₂, O₃, and NOx, impairs parasitoid efficiency by disrupting volatile-mediated host location and reducing biological control performance. Trichogramma wasps are generally effective biological control agents, but their success depends on the species used, target pest, crop, release density, and field conditions. Overall, species such as T. ostriniae, T. japonicum, and T. leucaniae show the strongest performance in several crops by increasing parasitism, reducing pest damage, and improving yield. This study highlights the successful integration of semiochemical cues in pest management programs and the effective utilization of Trichogramma in conjunction with entomopathogenic bacteria to control Lepidopteran pests. This approach contributes to the development of more effective pest management strategies, thereby promoting agricultural sustainability. Full article

Power-law kinetics are observed across a wide range of physical, chemical, biological, and engineering systems, yet the thermodynamic origin of the power-law exponent remains incompletely understood. This work proposes a thermodynamic hypothesis in which power-law behavior emerges naturally from correlation-dependent contributions to the Gibbs free energy. Rather than modifying the classical Boltzmann definition of entropy, a phenomenological Correlation Constant, χ, is introduced to quantify how accumulated microstate evolution influences the accessibility of future states. The resulting correlation entropy contribution produces a free-energy term that modifies the probability of subsequent transitions and leads naturally to power-law kinetic behavior. Positive values of χ correspond to cooperative evolution in which prior evolution promotes future evolution, while negative values correspond to self-limiting behavior in which prior evolution suppresses subsequent evolution. The conventional Arrhenius-Eyring description is recovered as the special case χ = 0. The resulting framework provides a thermodynamic interpretation of the power-law exponent, establishes a connection between entropy, free energy, and kinetic evolution, and offers a unified description applicable to degradation, relaxation, diffusion, fatigue, trapping, and other evolving processes. The present work is intended as a thermodynamic hypothesis motivating further experimental and theoretical investigation of correlation-dependent kinetics. Full article