Chitosan-based nanofibrous scaffolds for biomedical and pharmaceutical applications: A comprehensive review

Nowadays, there is a wide range of deficiencies in treatment of diseases. These limitations are correlated with the inefficient ability of current modalities in the prognosis, diagnosis, and treatment of diseases. Therefore, there is a fundamental need for the development of novel approaches to overcome the mentioned restrictions. Chitosan (CS) nanoparticles, with remarkable physicochemical and mechanical properties, are FDA-approved biomaterials with potential biomedical aspects, like serum stability, biocompatibility, biodegradability, mucoadhesivity, non-immunogenicity, anti-inflammatory, desirable pharmacokinetics and pharmacodynamics, etc. CS-based materials are mentioned as ideal bioactive materials for fabricating nanofibrous scaffolds. Sustained and controlled drug release and in situ gelation are other potential advantages of these scaffolds. This review highlights the latest advances in the fabrication of innovative CS-based nanofibrous scaffolds as potential bioactive materials in regenerative medicine and drug delivery systems, with an outlook on their future applications.

Molecular recognition of carbonate ion using a novel turn-on fluorescent probe

A novel turn-on fluorescent probe 3 was synthesized by condensing salicylaldehyde and nicotinic hydrazide for the selective detection of CO32- in aqueous medium. Probe 3 exhibited a turn-on fluorescence response toward CO32- with excellent selectivity, sensitivity (DL = 2.76 μM), and good reversibility. The binding constant (K) of probe 3 with CO32- was calculated to be 5 × 103 M-1 (log K 3.69). The 1:1 stoichiometry of the complex between probe 3 and CO32- ions was confirmed by Job's plot and ESI-MS spectra. Deprotonation and hydrogen-bonding interactions are involved in the recognition of CO32- ion, which was also suggested by 1H NMR, ESI-MS spectra, and Density Functional Theory (DFT) calculations. Moreover, an INHIBIT type molecular logic gate was constructed by using 3:CO32- and CH3COOH as inputs and current signal as output. Owing to the practical applications, probe 3 demonstrated its efficiency in quantifying CO32- ion in real water samples through standard addition method, thus showcasing its potential in real environment. Further, the MTT assay indicated very low cytotoxicity (IC50 = 1 mM) of probe 3 and also the cell imaging experiments demonstrated the effective sensing of CO32- ions with probe 3 in the biological systems.

Harnessing role of sesamol and its nanoformulations against neurodegenerative diseases

Sesamol is a lignan of sesame seeds and a natural phenolic molecule that has emerged as a useful medical agent. Sesamol is a non-toxic phytoconstituent, which exerts certain valuable effects in the management of cancer, diabetes, cardiovascular diseases, neurodegenerative diseases (NDs), etc. Sesamol is known to depict its neuroprotective role by various mechanisms, such as metabolic regulators, action on oxidative stress, neuroinflammation, etc. However, its poor oral bioavailability, rapid excretion (as conjugates), and susceptibility to gastric irritation/toxicity (particularly in rats' forestomach) may restrict its effectiveness. To overcome the associated limitations, novel drug delivery system-based formulations of sesamol are emerging and being researched extensively. These can conjugate with sesamol and enhance the bioavailability and solubility of free sesamol, along with delivery at the target site. In this review, we have summarized various research works highlighting the role of sesamol on various NDs, including Alzheimer's disease, Huntington's disease, Amyotrophic lateral sclerosis, and Parkinson's disease. Moreover, the formulation strategies and neuroprotective role of sesamol-based nano-formulations have also been discussed.

Identification of novel candidate targets for suppressing ovarian cancer progression through IL-33/ST2 axis components using the system biology approach

Background: Cancer-associated fibroblasts (CAFs) of ovarian cancer (OvC) are the most prevalent element of the tumor microenvironment (TM). By promoting angiogenesis, immunological suppression, and invasion, CAFs speed up the growth of tumors by changing the extracellular matrix's structure and composition and/or initiating the epithelial cells (EPT). IL-33/ST2 signaling has drawn a lot of attention since it acts as a pro-tumor alarmin and encourages spread by altering TM. Methods: Differentially expressed genes (DEGs) of the OvC tumor microenvironment were found in the GEO database, qRT-PCR, western blotting, and immunohistochemistry, and their presence and changes in healthy and tumor tissue content were examined. Primary cultures of healthy fibroblasts and CAFs obtained from healthy and tumor tissues retrieved from OvC samples were used for in vitro and in vivo investigations. Cultured primary human CAFs were utilized to investigate the regulation and the IL-33/ST2 axis role in the inflammation reactions. Results: Although ST2 and IL-33 expression was detected in both epithelial (EPT) and fibroblast cells of ovarian cancer, they are more abundant in CAFs. Lipopolysaccharides, serum amyloid A1, and IL-1β, the inflammatory mediators, could all induce IL-33 expression through NF-κB activation in human CAFs. In turn, via the ST2 receptor, IL-33 affected the production of IL-6, IL-1β, and PTGS2 in human CAFs via the MAPKs-NF-κB pathway. Conclusion: Our findings suggest that IL-33/ST2 is affected by the interaction of CAFs and epithelial cells inside the tumor microenvironment. Activation of this axis leads to increased expression of inflammatory factors in tumor CAFs and EPT cells. Therefore, targeting the IL-33/ST2 axis could have potential value in the prevention of OvC progression.

Relevance of Machine Learning to Predict the Inhibitory Activity of Small Thiazole Chemicals on Estrogen Receptor

BACKGROUND

Drug discovery requires the use of hybrid technologies for the discovery of new chemical substances. One of those interesting strategies is QSAR via applying an artificial intelligence system that effectively predicts how chemical alterations can impact biological activity via in-silico.

AIM

Our present study aimed to work on a trending machine learning approach with a new opensource data analysis python script for the discovery of anticancer lead via building the QSAR model by using 53 compounds of thiazole derivatives.

METHODS

A python script has been executed with 53 small thiazole chemicals using Google collaboratory interface. A total of 82 CDK molecular descriptors were downloaded from "chemdes" web server and used for our study. After training the model, we checked the model performance via cross-validation of the external test set.

RESULTS

The generated QSAR model afforded the ordinary least squares (OLS) regression as R² = 0.542, F=8.773, and adjusted R² (Q2) =0.481, std. error = 0.061, reg.coef_ developed were of, - 0.00064 (PC1), -0.07753 (PC2), -0.09078 (PC3), -0.08986 (PC4), 0.05044 (PC5), and reg.intercept_ of 4.79279 developed through stats models, formula module. The performance of test set prediction was done by multiple linear regression, support vector machine, and partial least square regression classifiers of sklearn module, which generated the model score of 0.5424, 0.6422 and 0.6422 respectively.

CONCLUSION

Hence, we conclude that the R2values (i.e. the model score) obtained using this script via three diverse algorithms were correlated well and there is not much difference between them and may be useful in the design of a similar group of thiazole derivatives as anticancer agents.

Nutraceuticals and mitochondrial oxidative stress: bridging the gap in the management of bronchial asthma

Asthma is a chronic inflammatory disease primarily characterized by inflammation and reversible bronchoconstriction. It is currently one of the leading causes of morbidity and mortality in the world. Oxidative stress further complicates the pathology of the disease. The current treatment strategies for asthma mainly involve the use of anti-inflammatory agents and bronchodilators. However, long-term usage of such medications is associated with severe adverse effects and complications. Hence, there is an urgent need to develop newer, novel, and safe treatment modalities for the management of asthma. This has therefore prompted further investigations and detailed research to identify and develop novel therapeutic interventions from potent untapped resources. This review focuses on the significance of oxidative stressors that are primarily derived from both mitochondrial and non-mitochondrial sources in initiating the clinical features of asthma. The review also discusses the biological scavenging system of the body and factors that may lead to its malfunction which could result in altered states. Furthermore, the review provides a detailed insight into the therapeutic role of nutraceuticals as an effective strategy to attenuate the deleterious effects of oxidative stress and may be used in the mitigation of the cardinal features of bronchial asthma.