Natural serine proteases and their applications in combating amyloid formation.

Background And Purpose: Amyloidosis is a group of diseases including diabetes type II and neurological disorders, such as Alzheimer's disease, Parkinson's disease, prion disease, etc., where a common trait is observed; accumulation of misfolded protein at different parts of the body, especially the brain which manifests the typical symptoms like dementia, movement disorders, etc. These misfolded proteins, named amyloids, are protease resistant and thus it becomes difficult to manage these diseases in vivo.

Exploring the amyloid degradation potential of nanoformulated carrageenan-bridging in vitro and in vivo perspectives.

Amyloids, with their β-sheet-rich structure, contribute to diabetes, neurodegenerative diseases, and amyloidosis by aggregating within diverse anatomical compartments. Insulin amyloid (IA), sharing structural resemblances with amyloids linked to neurological disorders, acts as a prototype, while compounds capable of degrading these fibrils hold promise as therapeutic agents for amyloidosis intervention. In this research, liposomal nanoformulated iota carrageenan (nCG) was formulated to disrupt insulin amyloids, demonstrating about a 17-20 % higher degradation efficacy compared to conventional carrageenan through thioflavin T fluorescence, dynamic light scattering analysis, and turbidity quantification.

NOSH-aspirin (NBS-1120) inhibits estrogen receptor negative breast cancer and i by modulating redox-sensitive signaling pathways.

Estrogen receptor (ER)-negative breast cancers are known to be aggressive and unresponsive to anti-estrogen therapy, and triple negative breast cancers are associated with poor prognosis and metastasis. Thus, new targeted therapies are needed. FOXM1 is abundantly expressed in human cancers and implicated in protecting tumor cells from oxidative stress by reducing the levels of intracellular reactive oxygen species (ROS).

Multiresolution directed transfer function approach for segment-wise seizure classification of epileptic EEG signal.

Currently, with the bloom in artificial intelligence (AI) algorithms, various human-centered smart systems can be utilized, especially in cognitive computing, for the detection of various chronic brain diseases such as epileptic seizure. The primary goal of this research article is to propose a novel human-centered cognitive computing (HCCC) method for segment-wise seizure classification by employing multiresolution extracted data with directed transfer function (DTF) features, termed as the multiresolution directed transfer function (MDTF) approach. Initially, the multiresolution information of the epileptic seizure signal is extracted using a multiresolution adaptive filtering (MRAF) method.

Identification of highly selective SIK1/2 inhibitors that modulate innate immune activation and suppress intestinal inflammation.

The salt-inducible kinases (SIK) 1-3 are key regulators of pro- versus anti-inflammatory cytokine responses during innate immune activation. The lack of highly SIK-family or SIK isoform-selective inhibitors suitable for repeat, oral dosing has limited the study of the optimal SIK isoform selectivity profile for suppressing inflammation in vivo. To overcome this challenge, we devised a structure-based design strategy for developing potent SIK inhibitors that are highly selective against other kinases by engaging two differentiating features of the SIK catalytic site.