Zeolite-based nanoparticles drug delivery systems in modern pharmaceutical research and environmental remediation.

This review explores the potential of zeolite-based nanoparticles in modern pharmaceutical research, focusing on their role in advanced drug delivery systems. Zeolites, integrated into polymeric materials, offer precise drug delivery capabilities due to their unique structural features, biocompatibility, and controllable properties. Additionally, zeolites demonstrate environmental remediation potential through ion exchange processes. Synthetic zeolites, with modified release mechanisms, possess distinctive optical and electronic properties, expanding their applications in various fields. The study details zeolites' significance across industrial and scientific domains, outlining synthesis methods and size control techniques. The review emphasizes successful encapsulation and functionalization strategies for drug delivery, highlighting their role in enhancing drug stability and enabling targeted delivery. Advanced characterization techniques contribute to a comprehensive understanding of zeolite-based drug delivery systems. Addressing potential carcinogenicity, the review discusses environmental impact and risk assessment, stressing the importance of safety considerations in nanoparticle research. In biomedical applications, zeolites play vital roles in antidiarrheal, antitumor, antibacterial, and MRI contrast agents. Clinical trials featuring zeolite-based interventions underscore zeolite's potential in addressing diverse medical challenges. In conclusion, zeolite-based nanoparticles emerge as promising tools for targeted drug delivery, showcasing diverse applications and therapeutic potentials. Despite challenges, their unique advantages position zeolites at the forefront of innovative drug delivery systems.

Design, Synthesis, and Biological Evaluation of Ferulic Acid-Piperazine Derivatives Targeting Pathological Hallmarks of Alzheimer's Disease.

Alzheimer's disease (AD) is the most prevalent cause of dementia and is characterized by low levels of acetyl and butyrylcholine, increased oxidative stress, inflammation, accumulation of metals, and aggregations of Aß and tau proteins. Current treatments for AD provide only symptomatic relief without impacting the pathological hallmarks of the disease. In our ongoing efforts to develop naturally inspired novel multitarget molecules for AD, through extensive medicinal chemistry efforts, we have developed 13a, harboring the key functional groups to provide not only symptomatic relief but also targeting oxidative stress, able to chelate iron, inhibiting NLRP3, and Aß1-42 aggregation in various AD models. 13a exhibited promising anticholinesterase activity against AChE (IC50 = 0.59 ± 0.19 µM) and BChE (IC50 = 5.02 ± 0.14 µM) with excellent antioxidant properties in DPPH assay (IC50 = 5.88 ± 0.21 µM) over ferulic acid (56.49 ± 0.62 µM). The molecular docking and dynamic simulations further corroborated the enzyme inhibition studies and confirmed the stability of these complexes. Importantly, in the PAMPA-BBB assay, 13a turned out to be a promising molecule that can efficiently cross the blood-brain barrier. Notably, 13a also exhibited iron-chelating properties. Furthermore, 13a effectively inhibited self- and metal-induced Aß1-42 aggregation. It is worth mentioning that 13a demonstrated no symptom of cytotoxicity up to 30 µM concentration in PC-12 cells. Additionally, 13a inhibited the NLRP3 inflammasome and mitigated mitochondrial-induced reactive oxygen species and mitochondrial membrane potential damage triggered by LPS and ATP in HMC-3 cells. 13a could effectively reduce mitochondrial and cellular reactive oxygen species (ROS) in the Drosophila model of AD. Finally, 13a was found to be efficacious in reversing memory impairment in a scopolamine-induced AD mouse model in the in vivo studies. In ex vivo assessments, 13a notably modulates the levels of superoxide, catalase, and malondialdehyde along with AChE and BChE. These findings revealed that 13a holds promise as a potential candidate for further development in AD management.

Dose optimization of second window indocyanine green in meningioma patients.

OBJECTIVE: Surgery remains the first line treatment for meningiomas and can benefit from fluorescence-guided surgical techniques such as second-window indocyanine green (SWIG). In the current study, we compared the use of the standard SWIG dose of 5.0 mg/kg relative to 2.5 mg/kg indocyanine green (ICG) in meningioma patients. METHODS: Patients were prospectively enrolled in an IRB-approved study of SWIG and received either the standard dose of 5.0 mg/kg or a reduced dose of 2.5 mg/kg of ICG around 24 h prior to their surgery. Intraoperative near-infrared fluorescence imaging was performed with exo- and endoscopic systems. Signal-to-background ratio (SBR) was calculated to quantify fluorescence and was compared between 5.0 mg/kg and 2.5 mg/kg ICG. All patients received pre-operative MRI and, in select cases, the pre-operative MRI was correlated to intraoperative fluorescence imaging. RESULTS/DISCUSSION: In the current study, we found no significant difference in the SBR of meningiomas in patients that were administered with either 5.0 mg/kg or 2.5 mg/kg ICG. However, in five patients that received the standard-dose SWIG regimen of 5.0 mg/kg ICG we observed dose-related fluorescence quenching - referred to as "inversion" - that interfered with tumor visualization during fluorescence-guided surgery (FGS). When correlated to pre-operative MRI, a similar rim pattern was observed around the primary tumor on T2 FLAIR, which, in retrospect, could be used as a predictor for inversion during FGS in meningioma patients receiving standard-dose ICG. CONCLUSION: This study demonstrated that a reduced ICG dose was as effective as standard-dose SWIG in meningioma patients. We therefore recommend to adjust the standard ICG dose for meningioma patients to 2.5 mg/kg particularly when rim enhancement is observed on pre-operative T2 FLAIR.

Evaluation of Physicochemical Properties of Ipsapirone Derivatives Based on Chromatographic and Chemometric Approaches.

Drug discovery is a challenging process, with many compounds failing to progress due to unmet pharmacokinetic criteria. Lipophilicity is an important physicochemical parameter that affects various pharmacokinetic processes, including absorption, metabolism, and excretion. This study evaluated the lipophilic properties of a library of ipsapirone derivatives that were previously synthesized to affect dopamine and serotonin receptors. Lipophilicity indices were determined using computational and chromatographic approaches. In addition, the affinity to human serum albumin (HSA) and phospholipids was assessed using biomimetic chromatography protocols. Quantitative Structure-Retention Relationship (QSRR) methodologies were used to determine the impact of theoretical descriptors on experimentally determined properties. A multiple linear regression (MLR) model was calculated to identify the most important features, and genetic algorithms (GAs) were used to assist in the selection of features. The resultant models showed commendable predictive accuracy, minimal error, and good concordance correlation coefficient values of 0.876, 0.149, and 0.930 for the validation group, respectively.

Berberine derivatives as inhibitors of acetylcholinesterase: A systematic review.

Alzheimer's disease (AD) is a chronic age-related neurodegenerative brain disorder characterized by the impairment of memory accompanied by worsening of thinking ability of an individual. The exact pathophysiology of AD is not fully understood. However low level of the neurotransmitter named acetylcholine (ACh), aggregation of Aß peptide into toxic Aß plaque, hyperphosphorylation of tau, bio-metal imbalance, and oxidative stress are the main hallmarks of this disease. Due to the complex pathophysiology of AD, no specific treatment is available in the market, and treatment is only limited to the symptomatic relief. So, there is an urgent need for the development of new drug candidate, which can have disease-modifying effect and improve learning and memory in AD patient. Therefore, berberine-based multifunction compounds with potential cholinesterase inhibitory properties were reviewed in this article. Structure-activity relationship (SAR) and biological activity provide highlights on the new derivatives used for the management of AD.

Tryptamine: A privileged scaffold for the management of Alzheimer's disease.

Alzheimer's disease (AD) is a chronic and irreversible neurodegenerative disease associated with aging. It is characterized by the progressive loss of memory and other cognitive functions. Although the exact etiology of AD is not well explored, several factors, such as the deposition of amyloid-ß (Aß) plaques, hyperphosphorylation of tau protein, presence of low levels of acetylcholine, and generation of oxidative stress, are key mediators in the progression of AD. Currently, the clinical treatment options for AD are limited and are based on cholinesterase (ChE) inhibitors (e.g., donepezil, rivastigmine, and galantamine), N-methyl- d-aspartic acid receptor antagonists (e.g., memantine), and the recently approved Aß modulator (e.g., aducanumab). Tryptamine (2-(1H-indol-3-yl)ethan-1-amine) is a small molecule that contains an indole nucleus and an ethylamine side chain. It is also the active metabolite of tryptophan. It possesses a wide range of biological activities related to neurodegenerative disorders, such as ChE inhibition, Aß aggregation inhibition, antioxidant effects, monoamine-oxidase inhibition, and neuroprotection. Several tryptamine-based hybrid analogs are currently being investigated as multifunctional agents for the development of novel hybrids for AD treatment. Thus, this review article aims to provide in-depth insights into the research progress and strategies for designing multifunctional agents used in Alzheimer's therapy.

Advances in AI-Driven Retention Prediction for Different Chromatographic Techniques: Unraveling the Complexity.

Retention prediction through Artificial intelligence (AI)-based techniques has gained exponential growth due to their abilities to process complex sets of data and ease the crucial task of identification and separation of compounds in most employed chromatographic techniques. Numerous approaches were reported for retention prediction in different chromatographic techniques, and consistent results demonstrated that the accuracy and effectiveness of deep learning models outclassed the linear machine learning models, mainly in liquid and gas chromatography, as ML algorithms use fewer complex data to train and predict information. Support Vector machine-based neural networks were found to be most utilized for the prediction of retention factors of different compounds in thin-layer chromatography. Cheminformatics, chemometrics, and hybrid approaches were also employed for the modeling and were more reliable in retention prediction over conventional models. Quantitative Structure Retention Relationship (QSRR) was also a potential method for predicting retention in different chromatographic techniques and determining the separation method for analytes. These techniques demonstrated the aids of incorporating QSRR with AI-driven techniques acquiring more precise retention predictions. This review aims at recent exploration of different AI-driven approaches employed for retention prediction in different chromatographic techniques, and due to the lack of summarized literature, it also aims at providing a comprehensive literature that will be highly useful for the society of scientists exploring the field of AI in analytical chemistry.

An Intelligent Bio-Inspired Autonomous Surveillance System Using Underwater Sensor Networks.

Energy efficiency is important for underwater sensor networks. Designing such networks is challenging due to underwater environmental traits that hinder network lifespan extension. Unlike terrestrial protocols, underwater settings require novel protocols due to slower signal propagation. To enhance energy efficiency in underwater sensor networks, ongoing research concentrates on developing innovative solutions. Thus, in this paper, an intelligent bio-inspired autonomous surveillance system using underwater sensor networks is proposed as an efficient method for data communication. The tunicate swarm algorithm is used for the election of the cluster heads by considering different parameters such as energy, distance, and density. Each layer has several clusters, each of which is led by a cluster head that continuously rotates in response to the fitness values of the SNs using the tunicate swarm algorithm. The performance of the proposed protocol is compared with existing methods such as EE-LHCR, EE-DBR, and DBR, and results show the network's lifespan is improved by the proposed work. Due to the effective fitness parameters during cluster head elections, our suggested protocol may more effectively achieve energy balance, resulting in a longer network lifespan.

Carbamate as a potential anti-Alzheimer's pharmacophore: A review.

Alzheimer's disease (AD) is a progressive age-related neurodegenerative brain disorder, which leads to loss of memory and other cognitive dysfunction. The underlying mechanisms of AD pathogenesis are very complex and still not fully explored. Cholinergic neuronal loss, accumulation of amyloid plaque, metal ions dyshomeostasis, tau hyperphosphorylation, oxidative stress, neuroinflammation, and mitochondrial dysfunction are major hallmarks of AD. The current treatment options for AD are acetylcholinesterase inhibitors (donepezil, rivastigmine, and galantamine) and NMDA receptor antagonists (memantine). These FDA-approved drugs mainly provide symptomatic relief without addressing the pathological aspects of disease progression. So, there is an urgent need for novel drug development that not only addresses the basic mechanisms of the disease but also shows the neuroprotective property. Various research groups across the globe are working on the development of multifunctional agents for AD amelioration using different core scaffolds for their design, and carbamate is among them. Rivastigmine was the first carbamate drug investigated for AD management. The carbamate fragment, a core scaffold of rivastigmine, act as a potential inhibitor of acetylcholinesterase. In this review, we summarize the last 10 years of research conducted on the modification of carbamate with different substituents which primarily target ChE inhibition, reduce oxidative stress, and modulate Aß aggregation.

Rationalizing mineral gypsum use through microbially enriched municipal solid waste compost for amelioration and regaining productivity potential of degraded alkali soils.

Reclamation of alkali soils to harness their productivity potential is more complex due to the presence of excess sodium ions, poor hydraulic conductivity and infiltration rate, resulting in poor plant growth and crop productivity. Sodic soil reclamation using inorganic ameliorants like mineral gypsum or phosphogypsum is beyond the reach of small and marginal farmers having alkali soils because of their higher market prices and shortage of availability. Conjoint use of inorganic and organic amendments can be a pragmatic solution for improving soil physico-chemical and biological properties and sustaining crop productivity. Municipal solid waste compost (MSWC) available in abundant quantity if enriched with the efficient halophilic microbial consortium and used in conjunction with a reduced dose of gypsum can be a cost-effective approach for sustainable reclamation of alkali soils and harnessing their productivity potential. Hence, a field experiment was conducted on a high alkali soil (pH2 9.2 ± 0.10), electrical conductivity (EC) 1.14 ± 0.12 dS m-1, exchangeable sodium percentage 48 ± 2.50 and organic carbon (0.30%) was conducted during 2018-19 to 2020-21 to study the combined effect inorganic and organic (enriched municipal solid waste compost (EMSWC)) amendments on amelioration of alkali soils and sustaining productivity of rice-wheat cropping system. Application of gypsum @ 25% GR + enriched MSW compost @ 10 t ha-1 (T6) showed significant improvement in soil physico-chemical and biological properties over the sole application of organic (T3 and T4), inorganic (T2) and control (T1). A significant improvement in soil fertility status in terms of available nitrogen and micronutrients as well as CO3, HCO3, Cl, Ca and Mg content were recorded with the combined application of organic and inorganic soil amendments (T5 and T6) over the sole application of mineral gypsum. Soil microbial biomass carbon (MBC), nitrogen (MBN) and phosphorus (MBP) improved significantly due to the application of EMSWC with gypsum over the application of gypsum only. Grain yield of rice and wheat increased significantly (P < 0.05) owing to the application of a reduced dose of gypsum (25% GR) and EMSWC @ 10 t ha-1 (T6) with values of 5.55 and 3.83 t ha-1, respectively over rest of the treatments. Three years economic analysis of the study revealed that treatments T6 and T5 gave the highest positive net return whereas it was lowest in treatment T1 and negative in treatment T2. The highest benefit-to-cost ratio (B:C) was obtained in treatments T6 and T5 which were significantly higher compared to the rest of the treatments.