Organocatalysed three-component modular synthesis of BN isosteres and BN-2,1-azaboranaphthalenes via Wolff-type rearrangement.

[2,1]-Azaboranaphthalenes represent unique boron-nitrogen (BN) isosteres of naphthalenes, attracting interest for the development of molecules with enhanced therapeutic potency. The existing synthetic strategies are generally two-component reactions with harsh conditions. Here we report an organocatalysed three-component modular synthesis of ring-fused BN isosteres and BN-2,1-azaboranaphthalenes following ring expansion of unstrained cyclic ketones (n = 4-8) via Wolff-type rearrangement.

Mannose-Decorated Stimuli-Responsive Fluorescent Poly(aminoamide) Microgels for Lectin Binding and Sensing.

Development of suitable carbohydrate-decorated, biocompatible, and stimuli-responsive fluorescent microgels that can selectively bind and detect proteins (such as lectins) is an important research topic. Herein, we report the development of mannose-decorated, dual-stimuli (temperature and pH)-responsive fluorescent poly(aminoamide) microgels, which can selectively bind to and thereby detect the presence of concanavalin A (Con A). The resultant stimuli-responsive microgels have a lower critical solution temperature (VPTT) of 37.

Multilocus genetic and functional profiling of Indian-origin Lentinula edodes strains: Implications for cultivation and nutraceutical breeding.

Lentinula edodes (shiitake mushroom) is a widely cultivated edible and medicinal fungus, valued for its bioactive compounds. While East Asian strains have been well studied, Indian populations remain under-characterized. This study explores the genetic and functional diversity of five Indian-origin L.

PTTG1 as a common promising target for PCOS, Ovarian Cancer, and Major Depressive Disorder patients.

Women are susceptible to hormonal imbalances and endocrine-related disorders such as Polycystic Ovary Syndrome (PCOS), Ovarian Cancer (OC), and Major Depressive Disorder (MDD). This study aims to identify gene-level interconnections among these conditions using omics-based bioinformatic approaches. Publicly available GEO datasets, viz.

AI-informed retinal biomarkers predict 10-year risk of onset of multiple hematological malignancies.

Background: Early detection of hematological malignancies improves long-term survival but remains a critical challenge due to heterogeneity in clinical presentation. Chronic inflammation is a key driver in hematologic cancers and is known to induce compensatory microvascular changes. High-resolution, non-invasive retinal imaging can allow the quantification of microvascular changes for the early detection of hematological malignancies.