Search Results (5,494)

Auxenochlorella pyrenoidosa, a promising edible bioresource, can be efficiently and safely cultivated using exogenous phytohormones to enhance its productivity. This study employed multi-omics analysis to systematically investigate the effects and mechanisms of exogenous trans-Zeatin (tZ) on the growth and metabolism of A. pyrenoidosa. Results demonstrated that 10 mg/L tZ significantly promoted algal growth, increasing biomass by 166 ± 3.35% at 72 hours (h), while concurrently elevating cellular soluble protein (SP), carbohydrate (CHO), and chlorophyll a (Chla) content. tZ also strengthened the antioxidant defense system, evidenced by reduced reactive oxygen species (ROS) levels, enhanced activities of antioxidant enzymes (superoxide dismutase (SOD) and catalase (CAT)), upregulation of glutathione metabolism, and decreased lipid peroxidation product (malondialdehyde (MDA)). Furthermore, tZ activated key metabolic pathways, including nitrogen metabolism, photosynthetic carbon fixation, and porphyrin biosynthesis, leading to the accumulation of arginine and polyamines, etc. This study reveals that tZ promotes microalgal growth by coordinately regulating carbon–nitrogen metabolic networks and antioxidant systems, providing a theoretical foundation for phytohormone-augmented microalgae cultivation technologies. Full article

Recent advances in microbial bioremediation have significantly enhanced the effectiveness of wastewater management, offering innovative and sustainable alternatives to conventional treatment methods. Microorganisms, including bacteria, fungi, and algae, are increasingly recognized for their remarkable ability to degrade, transform, and remove a broad spectrum of pollutants such as organic compounds, heavy metals, and emerging contaminants from wastewater. Cutting-edge research has led to the development of novel approaches such as bioaugmentation, bio-stimulation, and the use of genetically engineered microbes, which have improved the efficiency, specificity, and resilience of bioremediation processes. The application of microbial consortia and advanced bioreactor designs further optimizes pollutant removal under diverse environmental conditions. Additionally, omics technologies and systems biology are providing deeper insights into microbial community dynamics and metabolic pathways, enabling the fine-tuning of bioremediation strategies for targeted outcomes. Despite ongoing challenges related to scalability, environmental variability, and regulatory considerations, these advances are paving the way for more robust, cost-effective, and eco-friendly wastewater management solutions. Overall, the integration of innovative microbial technologies holds great promise for addressing global water quality challenges and promoting environmental sustainability. Full article

Ischemic stroke remains one of the most catastrophic diseases in neurology, in which, due to a disturbance in the cerebral blood flow, the brain is acutely deprived of its oxygen and glucose oligomer, which in turn rapidly leads to energetic collapse and progressive cellular death. There is now increasing evidence that this type of stroke is not simply a type of ‘oxidative stress’ but rather a programmable loss-of-redox homeostasis, within which electron flow and the balance of oxidants/reductants are cumulatively displaced at the level of the single molecule and at the level of the cellular area. The advances being made in cryo-electron microscopy, lipidomics, and spatial omics are coupled with the introduction of a redox code produced by the interaction of the couples NADH/NAD⁺, NADPH/NADP⁺, GSH/GSSG, BH₄/BH₂, and NO/SNO, which determine the end results of the fates of the neurons, glia, endothelium, and pericytes. Within the mitochondria, pathophysiological events, including reverse electron transport, succinate overflow, and permeability transition, are found to be the first events after reperfusion, while signals intercommunicating via ER–mitochondria contact, peroxisomes, and nanotunnels control injury propagation. At the level of the tissue, events such as the constriction of the pericytes, the degradation of the glycocalyx, and the formation of neutrophil extracellular traps underlie microvascular failure (at least), despite the effective recanalization of the vessels. Systemic influences such as microbiome products, oxidized lipids, and free mitochondrial DNA in cells determine the redox imbalance, but this generally occurs outside the brain. We aim to synthesize how the progressive stages of ischemic injury evolve from the cessation of flow to the collapse of the cell structure. Within seconds of injury, there is reverse electron transport (RET) through mitochondrial complex I, with bursts of superoxide (O₂•⁻) and hydrogen peroxide (H₂O₂) being produced, which depletes the stores of superoxide dismutase, catalase, and glutathione peroxidase. Accumulated succinate and iron-induced lipid peroxidation trigger ferroptosis, while xanthine oxidase and NOX2/NOX4, as well as uncoupled eNOS/nNOS, lead to oxidative and nitrosative stress. These cascades compromise the function of neuronal mitochondria, the glial antioxidant capacity, and endothelial–pericyte integrity, leading to the degradation of the glycocalyx with microvascular constriction. Stroke, therefore, represents a continuum of redox disequilibrium, a coordinated biochemical failure linking the mitochondrial metabolism with membrane integrity and vascular homeostasis. Full article

Background: Hepatocellular carcinoma (HCC) continues to be a major cause of cancer associated deaths worldwide, highlighting the need for new prognostic biomarkers and treatment strategies. Triaptosis, a recently characterized mode of regulated cell death, has shown potential as a therapeutic target in various malignancies, including HCC. Nevertheless, how long non-coding RNAs (lncRNAs) regulate triaptosis, as well as their function in HCC, is still not well understood. Methods: This study integrates bioinformatics and functional validation to delineate the interplay between lncRNAs and triaptosis in HCC progression. Results: Firstly, we confirm that pharmacologically inducing triaptosis, a process centrally mediated by ROS accumulation, with menadione sodium bisulfite (MSB) can inhibit HCC growth both in vitro and in vivo. Furthermore, single-cell RNA sequencing identifies a specific elevation of the triaptosis-related gene MTM1 in malignant hepatocytes. Through systematic bioinformatics analysis of TCGA data, we develop a 5-lncRNA prognostic signature (LINC01134, HPN-AS1, DDX11-AS1, AC009283.1, AC009005.1) with superior predictive power over conventional clinical parameters. Strikingly, functional studies reveal that LINC01134 acts as a crucial oncogenic driver and its depletion suppresses proliferation, migration, and invasion while sensitizing cells to triaptosis via MTM1-mediated PI(3)P catabolism. Conclusions: Collectively, our study confirms that triaptosis is a therapeutically targetable signaling in HCC and proposes LINC01134 as a biomarker and therapeutic target, offering new insights into lncRNA-mediated regulation of cell death for precision oncology. Full article

The growing demand for sustainable, health-promoting foods has intensified efforts to improve the antioxidant potential of berry crops through integrative agronomic, genomic, and breeding innovations. Berries are rich dietary sources of bioactive compounds that support human health and provide benefits far beyond basic nutrition. This review explores the diversity of major berry crops, including blueberries, raspberries, cranberries, blackberries, and grapes, with emphasis on their nutritional value and antioxidant profiles. It also examines their domestication history, wild relatives, and commercial cultivars, offering insight into the genetic and phenotypic diversity underlying their rich chemical composition. Furthermore, the review highlights the application of modern tools to enhance antioxidant content. By integrating agronomic practices such as seed priming and grafting, advanced molecular breeding technologies, including multi-omics, genome-wide association studies (GWAS), and genome editing, breeders and researchers can accelerate the development of high-value berry cultivars that combine superior nutritional quality, resilience to environmental stress, and sustainable productivity under the challenges posed by climate change. Full article

Multidrug-resistant (MDR) Streptococcus suis (S. suis) is a zoonotic pathogen capable of infecting pigs across all age groups, leading to conditions such as meningitis, arthritis, and endocarditis. In humans, infections can result in septic arthritis, meningitis, necrotizing fasciitis, and septicemia, which may be fatal. The absence of a complete genome sequence hinders comprehensive bioinformatic studies of MDR S. suis derived from pigs. In this study, we present the whole-genome sequence of MDR S. suis serotype 2 ST01 isolated from joint fluid samples obtained from pigs. Whole-genome analysis revealed that the ST01 chromosome carries 19 antibiotic resistance genes that confer resistance to major classes of antibiotic including aminoglycosides, tetracyclines, fluoroquinolones, lincosamides, polypeptide, and nitrofurans. Additionally, it contains 15 virulence factors associated with immune modulation, bacterial adherence, and stress survival. Whole-genome analysis identified 84 horizontal gene transfer elements in ST01 (comprising 28 genomic islands, 52 transposons, and 4 prophages), alongside mutations resulting in reduced virulence (302 instances) and loss of pathogenicity (34 instances). Furthermore, 18 antibiotic targets along with 21 lethal mutations were identified as potential targets for preventing, controlling, and treating infection caused by MDR S. suis serotype 2 ST01. In vivo infection experiments demonstrated that intraperitoneal inoculation with ST01 resulted in mortality among Kunming mice, with a median lethal dose (LD₅₀) of 5.62 × 10⁹ CFU/mL. Histopathological analysis revealed varying degrees of lesions in the infected organs of the mice. This study thus provides valuable insights into strategies aimed at combating S. suis infections and their transmission within swine populations. Full article

Artificial intelligence (AI) is increasingly transforming biomedical research and patient care by integrating complex biological, radiological, and healthcare information. In the field of viral respiratory infections, AI-driven approaches have shown great promise in elucidating the complexity of lung immune responses and the dynamic interplay between host and pathogen. Applications include predicting cytokine storm and acute respiratory distress syndrome (ARDS), integrating imaging findings with immunological and laboratory data, and identifying molecular and cellular signatures through single-cell and multi-omics analyses. Similar methodologies have been applied to influenza and respiratory syncytial virus (RSV), providing insights into the mechanisms distinguishing protective from maladaptive pulmonary immunity. This narrative review summarizes current evidence on how AI can evolve into a form of translational intelligence, capable of bridging mechanistic immunology with clinical application. The review explores AI-based models for disease severity prediction, patient stratification, and therapeutic response assessment, as well as emerging approaches in drug repurposing and vaccine response prediction. By integrating biological complexity with clinical context, AI offers new opportunities to uncover immune signatures predictive of antiviral or immunomodulatory efficacy and to guide personalized management strategies. Full article

Dengue virus (DENV) is a major global health concern, with pathogenesis driven by complex interactions between the virus, host genetics, and immune responses. Key determinants of disease severity include antibody-dependent enhancement (ADE), cross-reactive T cells, anti-NS1 antibodies, autoimmunity, and genetic predisposition, with the NS1 protein and its antibodies strongly implicated in severe dengue. This review highlights recent advances in our understanding of how DENV impacts host immune responses at cellular, molecular, and genetic levels. We particularly focus on how the virus interacts with the host, alters immune responses, and escapes immune detection. These factors are crucial for disease progression and immune dysfunction. The host mounts both innate and adaptive immune responses involving interferon signalling, cytokine production, antigen presentation, and T-cell activation. However, DENV evades immunity by suppressing interferon pathways, disrupting antigen presentation, and leveraging antibody-dependent enhancement (ADE), leading to immune dysregulation, prolonged viremia, and severe dengue. Gaining insight into these host-pathogen interactions is essential for understanding dengue pathogenesis for designing safer and more effective therapeutics. Furthermore, integrating omics approaches with immune response models shows promise for identifying early, reliable markers that can predict disease severity and guide treatment. A deeper understanding of these processes will support the development of personalised treatment strategies and enhance preparedness for future dengue outbreaks. Full article

While short-term faba bean feeding is known to improve fish texture, its long-term systemic effects and the underlying molecular mechanisms in Nile tilapia remain rarely explored. This knowledge gap is critical, given the potential for extended feeding to induce distinct metabolic reprogramming and trade-offs. Here, we present the first comprehensive study investigating the 180-day impact of a 60% FB-based diet (FBD) on Nile tilapia through an integrated analysis of phenotypic traits, muscle histology, metabolome, and transcriptome. Our results revealed a fundamental trade-off: FBD feeding induced hyperplasia-driven muscle remodeling, significantly enhancing textural properties (hardness, gumminess, chewiness) and increasing intramuscular fat and collagen content, but at the cost of suppressed growth and hepatosomatic index. Metabolomics identified 243 significantly altered metabolites, outlining a systemic metabolic shift characterized by activated lipid synthesis but inhibited amino acid and energy metabolism. This multi-omics integration nominated the chac1 gene as a novel key regulator for FB-induced muscle hyperplasia, a finding not previously reported in this context. We propose a mechanistic model wherein long-term FBD feeding coordinates lipid deposition, collagen accumulation, and chac1-mediated hyperplastic growth to remodel muscle texture. Our work provides new insights into the long-term metabolic trade-offs and molecular drivers of FB-induced flesh quality improvement, offering a theoretical foundation for developing optimized aquafeeds. Full article

The plant microbiome is pivotal to sustainable agriculture and global food security, yet some challenges hinder fully harnessing it for field-scale impact. These challenges span measurement and integration, ecological predictability and translation across environments and seasons. Key obstacles include technical challenges, notably overcoming the limits of current sequencing for low-abundance taxa and whole-community coverage, integrating multi-omics data to uncover functional traits, addressing spatiotemporal variability in microbial dynamics, deciphering the interplay between plant genotypes and microbial communities, and enforcing standardized controls, metadata, depth targets and reproducible workflows. The rise of synthetic biology, omics tools, and artificial intelligence offers promising avenues for engineering plant–microbe interactions, yet their adoption requires regulatory, ethical, and scalability issues alongside clear economic viability for end-users and explicit accounting for evolutionary dynamics, including microbial adaptation and horizontal gene transfer to ensure durability. Furthermore, there is a need to translate research findings into field-ready applications that are validated across various soils, genotypes, and climates, while ensuring that advances benefit diverse regions through global, interdisciplinary collaboration, fair access, and benefit-sharing. Therefore, this review synthesizes current barriers and promising experimental and computational strategies to advance plant microbiome research. Consequently, a roadmap for fostering resilient, climate-smart, and resource-efficient agricultural systems focused on benchmarked, field-validated workflows is proposed. Full article

Background: Qu was the core starter of traditional Chinese fermentation and had long relied on artisan experience, which led to limited batch stability and standardization. This review organized the preparation processes, microbial diversity, and application patterns of qu in foods from experience to science perspective. Methods: This work summarized typical process parameters for daqu, xiaoqu, hongqu, wheat bran or jiangqu, douchi qu, and qu for mold curd blocks used for furu. Parameters covered raw material moisture, bed thickness, aeration or turning, drying, final moisture, and classification by peak temperature. Multi-omics evidence was used to analyze the coupling of temperature regime, community assembly, and functional differentiation. Indicators for pigment or enzyme production efficiency and safety control such as citrinin in hongqu were included. Results: Daqu showed low, medium, and high temperature regimes. Thermal history governed differences in communities and enzyme profiles and determined downstream fermentation fitness. Xiaoqu rapidly established a three-stage symbiotic network of Rhizopus, Saccharomyces, and lactic acid bacteria, which supported integrated saccharification and alcohol fermentation. Hongqu centered on Monascus and achieved coordinated pigment and aroma formation with toxin risk control through programmed control of temperature, humidity, and final moisture. Wheat bran or jiangqu served as an enzyme production engine for salt-tolerant fermentation, and the combined effects of heat and humidity during the qu period, aeration, and bed loading determined hydrolysis efficiency in salt. Douchi and furu mold curd blocks used thin-layer cultivation and near-saturated humidity to achieve stable mold growth and reproducible interfacial moisture. Conclusions: Parameterizing and online monitoring of key variables in qu making built a process fingerprint with peak temperature, heating rate, and moisture rebound curve at its core. Standardization and functional customization guided by temperature regime, community, and function were the key path for the transition of qu from workshop practice to industry and from experience to science. This approach provided replicable solutions for flavor consistency and safety in alcoholic beverages, sauces, vinegars, and soybean products. Full article

Xanthoceras sorbifolium Bunge leaves (XBL), traditionally consumed as herbal tea, have attracted increasing attention as potential functional food ingredients for managing type 2 diabetes mellitus (T2DM). This study investigated the anti-diabetic effects of an aqueous XBL extract in T2DM rats induced with a high-fat, high-sucrose diet combined with streptozotocin. XBL administration significantly improved glycemic control, insulin sensitivity, lipid profiles, and pancreatic and renal histopathology. Integrated 16S rRNA sequencing and untargeted fecal metabolomics revealed the modulation of key metabolic pathways, including linoleic acid and histidine metabolism, and elevated production of short-chain fatty acids (SCFAs) such as acetate and propionate. XBL also enriched beneficial gut microbes including Prevotella, Lachnospiraceae_NK4A136_group, and [Eubacterium]_xylanophilum_group, whose abundance showed positive correlations with SCFA levels and metabolic improvements. These findings demonstrate that XBL ameliorates T2DM through gut microbiota–SCFA–metabolite interactions and suggest its potential as a natural, multi-target dietary strategy for metabolic health management. Full article

Myalgic Encephalomyelitis (ME), also known as chronic fatigue syndrome (CFS), is a debilitating and heterogeneous disorder marked by persistent fatigue, post-exertional malaise, cognitive impairment, and multisystem dysfunction. Despite its prevalence and impact, the molecular mechanisms underlying ME remain poorly understood. This review synthesizes current evidence on the role of DNA, both nuclear and mitochondrial, in the susceptibility and pathophysiology of ME. We examined genetic predispositions, including familial clustering and candidate gene associations, and highlighted emerging insights from genome-wide and multi-omics studies. Mitochondrial DNA variants and oxidative stress-related damage are discussed in relation to impaired bioenergetics and symptom severity. Epigenetic modifications, particularly DNA methylation dynamics and transposable element activation, are explored as mediators of gene–environment interactions and immune dysregulation. Finally, we explored the translational potential of DNA-based biomarkers and therapeutic targets, emphasizing the need for integrative molecular approaches to advance diagnosis and treatment. Understanding the DNA-associated mechanisms in ME offers a promising path toward precision medicine in post-viral chronic diseases. Full article

Background: Artificial intelligence (AI) has the potential to significantly enhance clinical decision-making in oncology. However, its application in renal cell carcinoma (RCC) remains limited. The ART (Artificial Intelligence in Renal Tumors) project is a Spanish, multi-institutional initiative aimed at developing a dynamic, transcriptomics-based AI model to guide systemic treatment decisions for patients with metastatic RCC (mRCC). Objective: The aim of this paper is to present the rationale, methodology, and early implementation challenges of the ART project, as discussed during a dedicated Think Tank session at the 2025 International Kidney Cancer Symposium Europe (IKCSEU25), and to gather expert insights on its clinical and regulatory viability. Design, Setting, and Participants: The ART project includes three phases: (1) retrospective algorithm training using clinical and transcriptomic data from completed trials; (2) a prospective, non-interventional study collecting multi-omic and clinical data from 500 patients across 30 centers; and (3) a future comparative analysis of ART-guided versus standard clinical decisions. The AI model is designed to evolve continuously through ongoing data integration. Results and Limitations: Experts underscored the importance of integrating multimodal data—including circulating biomarkers and immune profiling—while expressing concerns about the reliance on short-term endpoints. Key barriers identified included data harmonization, external validation, and regulatory uncertainty regarding adaptive algorithms. The absence of a clear approval pathway for non-static clinical decision support systems also poses a challenge. Despite limited initial funding, the ART platform has generated strong institutional engagement and may serve as a scalable model for clinician-oriented AI tools. Conclusions: The ART project represents an innovative approach to AI-driven personalization of kidney cancer treatment. Expert feedback from IKCSEU25 highlighted the scientific robustness of the initiative, while also emphasizing the need for broader validation, regulatory clarity, and the use of clinically meaningful endpoints to support real-world implementation. Patient Summary: Experts reviewed a new AI-based tool being developed in Spain to help doctors choose the best treatments for kidney cancer. The tool shows promise but needs further testing and must meet regulatory standards before it can be used in routine clinical care. Full article

Sour meat, a traditional fermented meat product, derives its unique attributes from the flavors developed during the fermentation process. This study systematically investigated the dynamic changes in volatile compounds and bacterial succession in pork sour meat during fermentation (0, 15, 30, and 45 days) using a combination of an electric nose (E-nose), an electric tongue (E-tongue), gas chromatography–ion mobility spectrometry (GC-IMS), gas chromatography–mass spectrometry (GC-MS), and 16S rRNA amplicon sequencing. The results showed that the E-nose and E-tongue effectively distinguished samples across fermentation stages. The pork sour meat was analyzed using GC-IMS and GC-MS, which identified 39 and 81 volatile compounds (VOCs), respectively, primarily esters, alcohols, and aldehydes, with esters being most abundant after 45 days of fermentation. A total of 18 and 25 volatile compounds, respectively, were identified by GC-IMS and GC-MS as differential VOCs (p < 0.05, VIP > 1) of the pork sour meat. α-diversity increased in both species’ richness and diversity over the course of fermentation, while β-diversity analysis further differentiated samples across stages. Firmicutes dominated the bacterial community, with Staphylococcus, Lactobacillus, and Weissella as the main genera. Pearson correlation analysis revealed distinct associations between bacteria and volatiles: Staphylococcus was positively associated with butyl acetate-D, ethyl acetate, isoamyl acetate, dihydroactinidiolide, and (E)-2-heptenal, while Lactobacillus and Weissella were positively associated with acetic acid. Additionally, Weissella showed positive correlations with eight volatile compounds: acetic acid, nonanal, benzyl alcohol, ethyl crotonate, isoamyl acetate, dihydroactinidiolide, octanal, and ethyl acetate. This study provides a comprehensive understanding of volatile compound evolution and bacterial succession in pork sour meat, thereby offering a scientific basis for understanding and regulating its flavor quality. Full article