Inspired by natural cellular compartments, nanoreactors are spatially confined nanostructures that precisely regulate chemical and biological reactions and act as high-performance catalytic nanocontainers. Multifunctional integration of these systems surmounts the inherent limitations of conventional therapeutic modalities. This review focuses on recent breakthroughs in organic and organic-inorganic hybrid nanoreactors, highlighting three core effects: (1) the spatial confinement effect, which elevates the reactant concentration, accelerates mass transfer, lowers activation energy, modulates electronic states, and boosts reaction rates by orders of magnitude; (2) the synergistic effect of active sites, which enables efficient cascade reactions via spatially segregated or hierarchical catalytic architectures; (3) the stimuli-responsive effect, which dynamically controls catalysis and cargo release under endogenous (pH, enzymes, ROS) or exogenous (light, temperature) cues. Typical nanoreactors (liposomes, polymeric micelles/vesicles, mesoporous silica, protein cages, and organic-inorganic hybrids) are systematically discussed regarding structural merits and biomedical applications in treating diabetes, rheumatoid arthritis (RA), chronic wound healing, cancer, and Alzheimer's disease (AD). Current challenges and future perspectives are also addressed. Intelligent nanoreactors are expected to offer immense potential for disease diagnosis and therapy.

Corpora amylacea or "wasteosomes" are discontinuous lipid labyrinth structures that are polyglucosan rich, retain cellular waste and are thought to be of astrocytic origin. Wasteosomes localize around periventricular (PV) regions, perivascular spaces (PVS), and sub-pial regions; and their accumulation has been found to correlate with aging, vascular disorders, neurodegenerative diseases, and conditions that impair sleep. White matter hyperintensities (WMHs) are diffuse hyperintense areas seen on T2-weighted or fluid-attenuated inversion recovery (FLAIR) magnetic resonance imaging (MRI) scans that represent damage to white matter. PV WMHs are known predictors of mild cognitive impairment, stroke, dementia and death. The relationship between wasteosome accumulation, PV WMHs, vascular pathology and PVS is currently unknown. For the first time, in a mixed diagnostic cohort of pathologically diagnosed: Alzheimer's disease (AD), cerebrovascular disease (CVD), mixed AD/CVD, and control tissue with no pathological diagnosis, we connected the histopathological wasteosome profile in periventricular brain sections in relation to 7T FLAIR-MRI confirmed PV WMHs, vascular sclerosis and PVS. Our results reveal wasteosomes accumulate in PV WMHs, are increased in proximity to large PV venules, and exhibit complex relationships with WMH severity, mixed pathology, sclerotic index and PVS. These findings provide novel insights into the pathophysiology underlying white matter injury.

Sepsis-associated acute kidney injury (SA-AKI) is a serious complication with high mortality and lacks effective diagnostic and treatment strategies. This study aims to investigate the role of the LINC00920/miR-6834-3p/CPN1 axis in SA-AKI and evaluate its diagnostic value. Clinical serum samples and in vitro cell models were used to explore the role of the LINC00920/miR-6834-3p/CPN1 axis in SA-AKI. Serum expression of LINC00920, miR-6834-3p and CPN1 was detected to analyze their expression patterns in SA-AKI, and their diagnostic value was evaluated to verify potential biomarker utility. Dual-luciferase reporter assay, mutant construct and rescue experiments were performed to confirm the regulatory relationship of the LINC00920/miR-6834-3p/CPN1 axis. Functional experiments were conducted to detect cell injury, macrophage polarization and NET formation, so as to clarify the biological function of the axis in SA-AKI progression. Clinical analysis showed LINC00920 and CPN1 were downregulated, miR-6834-3p upregulated in SA-AKI. LINC00920 was negatively correlated with SA-AKI severity, suggesting its association with disease progression. The LINC00920/miR-6834-3p/CPN1 panel had high diagnostic value for SA-AKI and severity (AUC = 0.913, 0.912). In vitro experiments confirmed LINC00920 acts as a ceRNA to sponge miR-6834-3p and upregulate CPN1, exerting a protective role in SA-AKI by alleviating cell injury, M1 polarization and NET formation. The LINC00920/miR-6834-3p/CPN1 axis regulates SA-AKI progression, correlates with disease severity, and is a promising diagnostic biomarker.

Patients who undergo hematopoietic stem cell transplantation (HSCT) face a high risk of acute kidney injury (AKI), which significantly increases the likelihood of developing chronic kidney disease (CKD). Proteinuria is also frequently observed after HSCT and is associated with an increased risk of CKD progression. Thrombotic microangiopathy (TMA), stemming from endothelial injury caused by factors such as total body irradiation (TBI), calcineurin inhibitors, tyrosine kinase inhibitors, and graft-versus-host disease, is a major contributor to both AKI and CKD. We report a case of a woman in her early thirties who developed progressive kidney dysfunction and subnephrotic-range proteinuria three months after HSCT. Kidney biopsy findings included marked mesangiolysis, endothelial cell detachment, subendothelial expansion, and diffuse segmental capillary microaneurysms, which are highly suggestive of TMA due to TBI administered as part of the myeloablative conditioning regimen prior to HSCT. She underwent conservative management for chronic kidney disease, but her kidney function progressively declined. In patients presenting with a progressive decline in kidney function following HSCT, TMA should be included in the differential diagnosis. A kidney biopsy is valuable for determining the underlying cause of HSCT-associated TMA, as treatment strategies vary depending on the etiology. Prominent mesangiolysis with capillary microaneurysms, as observed in this case and the previously reported irradiated patients, may serve as a distinctive histological marker of radiation nephropathy.

Fungal diseases in fruit crops compromise productivity even when synthetic fungicides are applied. However, growing health and environmental concerns have made such products less attractive to consumers. In this context, the present study aimed to extract and characterise the essential oil (EO) from leaves and flowers of African basil (Ocimum gratissimum L.) by hydrodistillation and to evaluate its bioactivity against the fungi Botrytis cinerea, Fusarium guttiforme and Colletotrichum musae. Average EO yields were 3.90% w/w (leaves) and 2.60% w/w (flowers). Chromatographic analysis identified four constituents, mainly mono- and sesquiterpenes, with eugenol as the major compound (> 80%). Both the EO and pure eugenol displayed fungicidal activity against F. guttiforme and C. musae at 0.50 and 0.80 µL mL[-1] (EO) and at 0.50 and 1.20 µL mL[-1] (eugenol), respectively. The EO and eugenol were fungistatic against B. cinerea in vitro. The EO also inhibited more than 95% of C. musae conidial germination from 0.20 µL mL[-1]. In vivo assays, the EO reduced anthracnose severity in bananas. Molecular docking studies revealed that germacrene D and (E)-caryophyllene exhibited the strongest binding affinities to the fungal CYP51 enzyme, with binding energies of - 7.6 and - 7.3 kcal/mol, respectively, indicating their potential as effective antifungal agents. These findings indicate that African basil EO is a promising biofungicide and could be strategically integrated into sustainable crop protection programmes.

Identifying blood groups accurately is critical for safe medical practices, especially in emergencies, surgeries, and prenatal care. Conventional methods often depend on visual inspection of agglutination reactions, which can be error-prone, particularly when using small sample volumes. In this work, we introduce an efficient and intelligent system for blood type detection that combines digital microfluidics with advanced deep learning and antigen-based decision logic. A Vision Transformer (ViT) model was trained to recognize agglutination patterns in droplet-based blood images, followed by an automated mapping of standard ABO/Rh rules to assign the corresponding blood group based on antigen presence. The proposed system achieved 100% accuracy specifically in detecting antigen-antibody agglutination reactions, with perfect scores across precision, recall, specificity, and F1-score. Our method reduces the need for large reagent volumes and minimizes testing cost, while also improving reliability. In future work, our aim is to embed this system into a compact, microfluidics paper-based device, enabling low-cost, AI-assisted blood typing in portable point of care settings.

Grapevine red blotch disease (GRBD) poses a serious threat to viticulture in the United States. Grapevine red blotch virus (GRBV), a member species of Grablovirus vitis (family Geminiviridae), the causal agent of GRBD, disrupts grapevine physiology and metabolism, thereby interfering with the natural processes of fruit ripening. To date, there is limited knowledge about how grape maturity stages influence the timing of changes in viral load and disease progression. This study elucidates the effect of fruit maturity stages on GRBV accumulation in Vitis vinifera L. cv. Merlot grapevines in a Central Coast vineyard in California. Petioles from six basal leaves at random from previously GRBV-infected vines were collected at pre-véraison, véraison, post-véraison, and harvest stages, across two years (2021 and 2022). The viral copy number was quantified using digital PCR. The study identified significant differences (p < 0.05) in GRBV copy number across different maturity stages in 2021, irrespective of the year of infection. The lowest viral load was observed during the pre-véraison stage, and the highest at harvest, indicating progressive viral accumulation as the grapevines development progressed. In 2022, however, no significant difference in viral load across maturity stages was detected, an outcome attributed to extreme heat spikes coinciding with sampling periods. Our findings highlight the interplay between GRBV accumulation, grape development, and environmental parameters.

We propose a five-dimensional stochastic time-delay differential equation model that includes virus-to-cell infection, silent and active cell-cell transmissions and CTL immune response. Using mathematical methods, the non-degenerate five-dimensional stochastic delay differential equation model is transformed into a degenerate eight-dimensional stochastic differential equation model. The existence of a unique global positive solution is demonstrated. Then, by establishing a suitable Lyapunov function, we obtain the existence of a stationary Markov process when the stochastic CTL-activated reproduction number is greater than one. Additionally, we derive a critical condition for virus extinction using spectral radius analysis method and the law of large numbers theorem. Finally, through numerical simulations, we explore the impacts of random perturbations and cell-cell transmission on the dynamic behaviour of the model, and investigate the effect of time delays on T-cell count and viral load. Furthermore, ensemble simulations quantify viral clearance probabilities relative to the clinical detection limit, revealing that CTL-mediated immunity utilizes environmental stochasticity more efficiently than B-cell-mediated mechanisms to accelerate viral clearance.

Antimicrobial peptides (AMPs) represent a promising class of alternatives to conventional antibiotics. In this study, we compared the structural and functional properties of three synthetic undecapeptides: the anionic Cn-AMP2 and its N-terminally acetylated derivative (Ac-CnAMP2), versus the cationic α-helical peptide BP52. While BP52 exhibited strong antibacterial activity against both Gram-positive and Gram-negative bacteria, Cn-AMP2 and Ac-CnAMP2 showed no measurable antibacterial effects up to 128µM. Hemolysis assays revealed that BP52 caused mild to moderate lysis of red blood cells, whereas the anionic peptides were non-hemolytic. Molecular dynamics simulations confirmed the enhanced membrane insertion, clustering behavior, and bilayer disruption induced by BP52, in contrast to the limited interaction profiles of Cn-AMP2. These findings underscore the importance of positive charge, helical conformation, and amphipathic topology in driving membrane action and offer insights for designing optimized AMP-based therapeutics.

Multidrug-resistant (MDR) pathogens represent a major global health threat, necessitating the development of alternative therapeutic strategies. Drug repurposing has emerged as a promising approach to identify non-antibiotic agents with antimicrobial and antivirulence potential. Sodium-glucose cotransporter-2 (SGLT-2) inhibitors, widely used as antidiabetic agents, have recently attracted attention due to their potential antimicrobial properties. However, evidence regarding the antimicrobial activity of SGLT-2 inhibitors, particularly empagliflozin (EMP), remains limited. This study aimed to evaluate the in vitro antimicrobial and antibiofilm effects of EMP against clinical methicillin-resistant Staphylococcus aureus (MRSA) and Acinetobacter baumannii isolates. Minimum inhibitory concentrations (MICs) of empagliflozin were determined using the broth microdilution method. The antibiofilm activity of EMP was assessed spectrophotometrically, while its effect on bacterial cell viability was evaluated using a fluorometric resazurin assay. Additionally, changes in the expression of biofilm-related genes (icaA, icaD, bap, and adeG) were analyzed by real-time quantitative polymerase chain reaction (RT-qPCR). Empagliflozin demonstrated antimicrobial activity against tested clinical isolates MRSA (n = 3) and A. baumannii isolates (n = 3), with MIC values ranging from 3125 to 6250 µg/mL. EMP significantly inhibited biofilm formation in MRSA and A. baumannii strains by 79% and 85%, respectively. Gene expression analysis revealed downregulation of icaA and icaD in MRSA isolates, while bap and adeG expression levels were reduced by 85% and 64%, respectively, in A. baumannii strains. These preliminary and in vitro findings showed that empagliflozin could be a potential candidate for combating MDR pathogens. Further studies will be required to clarify its antimicrobial potential and underlying mechanisms of action.

The incorporation of artificial intelligence (AI) and machine learning (ML) into microalgal research is transforming biomass generation, biofuel synthesis, and wastewater remediation strategies. Sophisticated ML techniques, such as artificial neural networks (ANN), support vector machines (SVM), and genetic algorithms (GA), facilitate precise simulation and forecasting of highly intricate microalgal systems. Although constraints related to data accessibility and model scalability persist, ML-based methodologies are increasingly demonstrating their value in enhancing the sustainability and operational efficiency of microalgal processes. Simultaneously, technoeconomic analysis (TEA) has become an indispensable framework for assessing biorefinery viability through systematic evaluation of life-cycle environmental burdens. Recent progress in TEA methodologies has strengthened iterative design optimization, uncertainty quantification, and user accessibility via open-source computational platforms. Broader systems boundaries now account for policy mechanisms, performance during end-use phase, and international market dynamics, thereby reinforcing TEA's contribution to sustainable bioeconomic advancement. Collectively, these computational and analytical innovations are expediting the deployment of scalable and economically feasible microalgal technologies.Highlights The convergence of AI/ML technologies significantly advances microalgal biomass enhancement and biofuel process optimization. Chlorella remains a prominent genus investigated for biodiesel application owing to its elevated lipid accumulation and productivity. ML approaches, including ANN and SVM, effectively represent and simulate complex microalgal cultivation systems. Bibliometric evaluations indicate a rising research trajectory in AI/ML-driven microalgal studies. Persistent limitations include restricted data availability and challenges in scaling AI/ML frameworks to practical industrial environments.

Vibrio parahaemolyticus, a globally distributed bacterium in estuarine and coastal waters, poses a significant threat to seafood safety. The spread of antimicrobial resistance (AMR) in V. parahaemolyticus transcends phylogenetic, geographic, and ecological boundaries, raising concerns about its impact on marine ecosystems. This study investigated the prevalence and AMR profiles of V. parahaemolyticus in seafood in retail markets in Zhangzhou City, China. A total of 288 aquatic samples were collected aseptically from July 2023 to June 2024. Sixty-one V. parahaemolyticus isolates were identified using standard methods (cultural, biochemical, PCR) and characterized for virulence genes, AMR genes, antibiotic susceptibility, and molecular type. Multi-drug resistance (MDR) was then analyzed. The overall isolation rate of V. parahaemolyticus was 21% (61/288). A significant proportion of isolates exhibited high resistance to minocycline (97%), penicillin (93%), and cefazolin (90%). Lower resistance rates were observed for piperacillin (3%), ceftriaxone (5%), ceftazidime (7%), and cefoperazone (7%). Multi-antimicrobial resistance (MAR) indices revealed that 54% of isolates were resistant to more than ten antimicrobials. ERIC-PCR and RAPD typing grouped the isolates into four clusters each, with the majority (86.89% and 88.13%, respectively) belonging to Group I, indicating a high degree of genetic similarity among many isolates. The high prevalence of MDR V. parahaemolyticus in retail seafood suggests excessive antimicrobial use in aquaculture practices within this region. Effective antimicrobial stewardship programs, coupled with comprehensive surveillance, are urgently needed to mitigate the development and spread of AMR in V. parahaemolyticus and safeguard both human health and the health of marine ecosystems from pollution linked to aquaculture practices.