1,2,3-Triazole-tethered fluoroquinolone analogues with antibacterial potential: synthesis and cytotoxicity investigations.

The antibacterial efficacy of some newly developed bis- and C3-carboxylic moieties of fluoroquinolone-linked triazole conjugates was studied. Twenty compounds from two different series of triazoles were synthesized using click chemistry and evaluated for their antibacterial activity against a Gram-positive strain, (ATCC29212), and its clinical isolate and a Gram-negative bacterial strain, (ATCC25922), and its clinical isolate. Among the compounds, 7, 9a, 9d, 9i, 10(a-d), and 10i showed excellent activity with MIC values of up to 6.

Design and Synthesis of Topoisomerases-Histone Deacetylase Dual Targeted Quinoline-Bridged Hydroxamates as Anticancer Agents.

The multifactorial nature of cancer requires treatment that involves simultaneous targeting of associated overexpressed proteins and cell signaling pathways, possibly leading to synergistic effects. Herein, we present a systematic study that involves the simultaneous inhibition of human topoisomerases (hTopos) and histone deacetylases (HDACs) by multitargeted quinoline-bridged hydroxamic acid derivatives. These compounds were rationally designed considering pharmacophoric features and catalytic sites of the cross-talk proteins, synthesized, and assessed for their anticancer potential.

UTF1 Expression is Important for the Generation and Maintenance of Human iPSCs.

Background: Undifferentiated embryonic cell transcription factor 1 (UTF1) is predominantly expressed in pluripotent stem cells and plays a vital role in embryonic development and pluripotency maintenance. Despite its established importance in murine models, the role of UTF1 on human induced pluripotent stem cells (iPSCs) has not been comprehensively studied.

Methods: This study utilized CRISPR/Cas9 gene editing to create UTF1 knockout in human fibroblasts and iPSCs.

Explainable artificial intelligence with UNet based segmentation and Bayesian machine learning for classification of brain tumors using MRI images.

Detecting brain tumours (BT) early improves treatment possibilities and increases patient survival rates. Magnetic resonance imaging (MRI) scanning offers more comprehensive information, such as better contrast and clarity, than any alternative scanning process. Manually separating BTs from several MRI images gathered in medical practice for cancer analysis is challenging and time-consuming.

Fusion of transfer learning with nature-inspired dandelion algorithm for autism spectrum disorder detection and classification using facial features.

Autism spectrum disorder (ASD) is a neurologic disorder considered to cause discrepancies in physical activities, social skills, and cognition. There is no specific medicine for treating this disorder; early intervention is critical to improving brain function. Additionally, the lack of a clinical test for detecting ASD makes diagnosis challenging.