Vesicles of yeast cell wall-sitagliptin to alleviate neuroinflammation in Alzheimer's disease

Saccharomyces cerevisiae-derived vesicles loaded with dextromethorphan as a candidate for the management of neuroinflammation related to Alzheimer's disease

Alzheimer's disease (AD) is a neurodegenerative disease that is associated with neuroinflammation. Dextromethorphan (DXM) exerts neuroprotective effects in many central nervous system injuries and neurodegenerative diseases. The cell wall of Saccharomyces cerevisiae is a cell-based drug delivery system that can be a suitable candidate for targeted drug delivery to the site of inflammation. In this study, nanoparticles (NPs) were prepared from Saccharomyces cerevisiae cell walls, coated with polysorbate-80, and loaded with DXM. NPs had favorable hemolytic behavior with a particle size distribution of 187.25 ± 73.37 nm and a zeta potential of +4.3 mV. Pathological examination in a mouse model of neuroinflammation showed that NPs had the ability to reduce brain inflammation and the adverse effects of DXM.

Toward the Integration of Machine Learning and Molecular Modeling for Designing Drug Delivery Nanocarriers

The pioneering work on liposomes in the 1960s and subsequent research in controlled drug release systems significantly advances the development of nanocarriers (NCs) for drug delivery. This field is evolved to include a diverse array of nanocarriers such as liposomes, polymeric nanoparticles, dendrimers, and more, each tailored to specific therapeutic applications. Despite significant achievements, the clinical translation of nanocarriers is limited, primarily due to the low efficiency of drug delivery and an incomplete understanding of nanocarrier interactions with biological systems. Addressing these challenges requires interdisciplinary collaboration and a deep understanding of the nano-bio interface. To enhance nanocarrier design, scientists employ both physics-based and data-driven models. Physics-based models provide detailed insights into chemical reactions and interactions at atomic and molecular scales, while data-driven models leverage machine learning to analyze large datasets and uncover hidden mechanisms. The integration of these models presents challenges such as harmonizing different modeling approaches and ensuring model validation and generalization across biological systems. However, this integration is crucial for developing effective and targeted nanocarrier systems. By integrating these approaches with enhanced data infrastructure, explainable AI, computational advances, and machine learning potentials, researchers can develop innovative nanomedicine solutions, ultimately improving therapeutic outcomes.

Mixed-Micelle in Situ Gel as a Candidate for Oral Inflammatory Ulcerative Diseases

The current treatment for oral inflammatory ulcerative diseases has limitations. In situ forming hydrogels have shown great potential to deliver therapeutic substances for drug delivery to the buccal cavity. This study aimed to prepare and characterize lipid- and surfactant-based mixed micelle in situ gel (MIG) and evaluate whether it can offer more favorable properties than the in situ gel for effective treatment of the disease. Dexamethasone was incorporated into the MIGs particles, based on Poloxamer 407 and chitosan. The lower gelation time at 37 ℃ was considered a criterion to select superior formulations among the different lipid- and surfactant-based candidates. Further characterization was performed to evaluate the opted formulations regarding morphology, physical stability, rheology, texture, and release profile. All formulations were thermoresponsive and had a shorter gelation time as the temperature increased. Dexamethasone was released in a highly controlled manner, and morphological evaluation revealed that the mixed micelle in situ gels had spherical nanoparticles. Thixotropic behavior was observed in all MIGs, indicating a prolonged retention time of the formulation after oral administration. This study has shown that among different MIGs, the one with oleic acid is a more promising candidate than the in situ gel and other MIGs for drug delivery to the buccal cavity.

Cell primitive-based biomimetic nanomaterials for Alzheimer's disease targeting and therapy

Alzheimer's disease (AD) is a progressive neurodegenerative disorder, which is not just confined to the older population. Although developments have been made in AD treatment, various limitations remain to be addressed. These are partly contributed by biological hurdles, such as the blood-brain barrier and peripheral side effects, as well as by lack of carriers that can efficiently deliver the therapeutics to the brain while preserving their therapeutic efficacy. The increasing AD prevalence and the unavailability of effective treatments have encouraged researchers to develop improved, convenient, and affordable therapies. Functional materials based on primitive cells and nanotechnology are emerging as attractive therapeutics in AD treatment. Cell primitives possess distinct biological functions, including long-term circulation, lesion site targeting, and immune suppression. This review summarizes the challenges in the delivery of AD drugs and recent advances in cell primitive-based materials for AD treatment. Various cell primitives, such as cells, extracellular vesicles, and cell membranes, are presented together with their distinctive biological functions and construction strategies. Moreover, future research directions are discussed on the basis of foreseeable challenges and perspectives.

Knowledge Gaps in Generating Cell-Based Drug Delivery Systems and a Possible Meeting with Artificial Intelligence

Cell-based drug delivery systems are new strategies in targeted delivery in which cells or cell-membrane-derived systems are used as carriers and release their cargo in a controlled manner. Recently, great attention has been directed to cells as carrier systems for treating several diseases. There are various challenges in the development of cell-based drug delivery systems. The prediction of the properties of these platforms is a prerequisite step in their development to reduce undesirable effects. Integrating nanotechnology and artificial intelligence leads to more innovative technologies. Artificial intelligence quickly mines data and makes decisions more quickly and accurately. Machine learning as a subset of the broader artificial intelligence has been used in nanomedicine to design safer nanomaterials. Here, how challenges of developing cell-based drug delivery systems can be solved with potential predictive models of artificial intelligence and machine learning is portrayed. The most famous cell-based drug delivery systems and their challenges are described. Last but not least, artificial intelligence and most of its types used in nanomedicine are highlighted. The present Review has shown the challenges of developing cells or their derivatives as carriers and how they can be used with potential predictive models of artificial intelligence and machine learning.

Metformin-loaded nanoerythrosomes: An erythrocyte-based drug delivery system as a therapeutic tool for glioma

Glioma is an intra-cranial malignancy with the origin of neural stem cells or precursor cells, the most prevalent brain tumor worldwide. Glioblastoma, the fourth-grade glioma, is a common brain tumor whose incidence rate is 5-7 people per 100,000 populations annually. Despite their high mortality rate, all efforts for treatment have yet to achieve any desirable clinical outcome. The Wnt signaling pathway is a conserved pathway among species that seems to be a candidate for cancer therapy by its inhibition. Metformin is a known inhibitor of the Wnt signaling pathway. Its effects on glioma treatment have been observed in cellular, animal, and clinical experiments. Nanoerythrosomes are drug carriers obtained from the cellular membrane of red blood cells in nano size which can offer several characteristics to deliver metformin to brain tumors. They are good at loading and carrying hydrophilic drugs, they can protect metformin from its metabolizing enzymes, which are present in the blood-brain barrier, and they can extend the period of metformin presence in circulation. In this study, nanoerythrosomes were prepared by using the hypotonic buffer. They had particle sizes in the range of 97.1 ± 34.2 nm, and their loading efficiency and loading capacity were 72.6% and 1.66%, respectively. Nanoerythrosomes could reserve metformin in their structure for a long time, and only 50% of metformin was released after 30 h. Moreover, they released metformin at a low and approximately constant rate. Besides, nanoerythrosomes could tolerate various kinds of stress and maintain most of the drug in their structure. Altogether, nanoerythrosome can be a suitable drug delivery system to deliver therapeutic amounts of metformin to various tissues.

β-Glucan attenuates cognitive impairment of APP/PS1 mice via regulating intestinal flora and its metabolites

BACKGROUND

The intestinal flora has been shown to be involved in the progression of Alzheimer's disease (AD) and can be improved by β-glucan, a polysaccharide derived from Saccharomyces cerevisiae, which affects cognitive function through the intestinal flora. However, it is not known if this effect of β-glucan is involved in AD.

METHOD

This study used behavioral testing to measure cognitive function. After that, high-throughput 16 S rRNA gene sequencing and GC-MS were used to analyze the intestinal microbiota and metabolite SCFAs of AD model mice, and further explore the relationship between intestinal flora and neuroinflammation. Finally, the expressions of inflammatory factors in the mouse brain were detected by Western blot and Elisa methods.

RESULTS

We found that appropriate supplementation of β-glucan during the progression of AD can improve cognitive impairment and reduce A β plaque deposition. In addition, supplementation of β-glucan can also promote changes in the composition of the intestinal flora, thereby changing the flora metabolites in the intestinal content and reduce the activation of inflammatory factors and microglia in the cerebral cortex and hippocampus through the brain-gut axis. While reducing the expression of inflammatory factors in the hippocampus and cerebral cortex, thereby controlling neuroinflammation.

CONCLUSION

The imbalance of the gut microbiota and metabolites plays a role in the progression of AD; β-glucan blocks the development of AD by improving the gut microbiota and its metabolites and reducing neuroinflammation. β-Glucan is a potential strategy for the treatment of AD by reshaping the gut microbiota and improving its metabolites.