Biofabrication paradigms in corneal regeneration: bridging bioprinting techniques, natural bioinks, and stem cell therapeutics.

Corneal diseases are a major cause of vision loss worldwide. Traditional methods like corneal transplants from donors are effective but face challenges like limited donor availability and the risk of graft rejection. Therefore, new treatment methods are essential. This review examines the growing field of bioprinting and biofabrication in corneal tissue engineering. We begin by discussing various bioprinting methods such as stereolithography, inkjet, and extrusion printing, highlighting their strengths and weaknesses for eye-related uses. We also explore how biological tissues are made suitable for bioprinting through a process called decellularization, which can be achieved using chemical, physical, or biological methods. The review then looks at natural materials, known as bioinks, used in bioprinting. We focus on materials like gelatin, collagen, fibrin, chitin, chitosan, silk fibroin, and alginate, examining their mechanical and biological properties. The importance of hydrogel scaffolds, particularly those based on collagen and other materials, is also discussed in the context of repairing corneal tissue. Another key area we cover is the use of stem cells in corneal regeneration. We pay special attention to limbal epithelial stem cells and mesenchymal stromal cells, highlighting their roles in this process. The review concludes with an overview of the latest advancements in corneal tissue bioprinting, from early techniques to advanced methods of delivering stem cells using bioengineered materials. In summary, this review presents the current state and future potential of bioprinting and biofabrication in creating functional corneal tissues, highlighting new developments and ongoing challenges with a view towards restoring vision.

Repurposing of digoxin in pain and inflammation: An evidence-based study.

In recent years, the drug repositioning strategy has gained considerable attention in the drug discovery process that involves establishing new therapeutic uses of already known drugs. In line with this, we have identified digoxin a cardiac glycoside, as a potent inhibitor of soluble epoxide hydrolase (sEH) enzyme employing in silico high throughput screening protocols and further confirmed using in vitro cell-free sEH inhibitory assay and in vivo preclinical studies in rodents for its repurposing in hyperalgesia, inflammation, and related disorders. Oral administration of digoxin at dose 0.2 mg/kg significantly reduced (p < .0001) the allodynia in mice induced by using hot plate (3.6 ± 1.9) and tail-flick test (7.58 ± 0.9). In addition, digoxin at a dose of 0.2 mg/kg showed marked reduction (94%, p < .0001) in acetic acid-induced abdominal contraction in rats. Further, digoxin also demonstrated antipyretic activity (37.04 ± 0.2, p < .0001) and showed notable reduction (0.60 ± 0.06) in carrageenan-induced paw edema in rats. Also, the histopathological evaluation revealed that digoxin treatment attenuated the edema, neutrophil infiltration, and alveolar septal thickening in lung tissue. These findings are novel and highlight the newer insights towards repurposing digoxin as a new lead in the treatment of hyperalgesia, inflammation, and related disorders.

Use of Diverse Chemometric and Validation Methods to Accurately Predict Human Urotensin-II Receptor Antagonist Activity.

Despite being identified as the most potent receptor related to vasoconstriction, human urotensin-II receptor (hUT) has not been fully explored as a target for the treatment of cardiovascular diseases. In view of this and with an aim to identify precise structural requirements for binding of hUT antagonists, we endeavoured to develop, for the first time, multivariate QSAR models using chemometric methods like partial least squares (PLS) and feed-forward neural network (FFNN). A set of 48 pyrrolidine derivatives having hUT binding affinity was used for multivariate model development. The accuracy and predictability of the developed models was evaluated using crossvalidation. The PLS model showed good correlation between selected descriptors and Ki values (r(2) =0.745 and r(2) (CV) =0.773). However, the predictive performance of FFNN was better than the PLS technique with r(2) =0.810. The study clearly suggests the role of lipophilic and steric descriptors in the ligand-hUT interactions. The QSAR models generated can be successfully extended to predict the binding affinities and for the effective design of novel hUT antagonists.

Neglected disease - african sleeping sickness: recent synthetic and modeling advances.

Human African Trypanosomiasis (HAT) also called sleeping sickness is caused by subspecies of the parasitic hemoflagellate Trypanosoma brucei that mostly occurs in sub-Saharan Africa. The current chemotherapy of the human trypanosomiases relies on only six drugs, five of which have been developed more than 30 years ago, have undesirable toxic side effects and most of them show drug-resistance. Though development of new anti-trypanosomal drugs seems to be a priority area research in this area has lagged far behind. The given review mainly focus upon the recent synthetic and computer based approaches made by various research groups for the development of newer anti-trypanosomal analogues which may have improved efficacy and oral bioavailability than the present ones. The given paper also attempts to investigate the relationship between the various physiochemical parameters and anti-trypanosomal activity that may be helpful in development of potent anti-trypanosomal agents against sleeping sickness.

Development of a robust QSAR model to predict the affinity of pyrrolidine analogs for dipeptidyl peptidase IV (DPP- IV).

QSAR analysis using multiple linear regression and partial least squares methods were conducted on a data set of 47 pyrrolidine analogs acting as DPP IV inhibitors. The QSAR models generated (both MLR and PLS) were robust with statistically significant s, F, r, r(2) and r(2) (CV) values. The analysis helped to ascertain the role of shape flexibility index, Ipso atom E-state index and electrostatic parameters like dipole moment, in determining the activity of DPP IV inhibitors. In addition to QSAR modeling, Lipinski's rule of five was also employed to check the pharmacokinetic profile of DPP IV inhibitors. Since none of the compounds violated the Lipinski's rule of five indicating that the DPP IV inhibitors reported herein have sound pharmacokinetic profile and can be considered as potential drug candidates for diabetes mellitus Type II.