Rheumatoid arthritis (RA) is a chronic autoimmune disease with progressive joint damage, functional disability and systemic comorbidity. Available therapies are not satisfactory, including low rates of remission and about 30% of patients with poor response to first-line treatment. Thus, more effective therapeutic strategies are urgently needed. Sanguinarine, a benzophenanthridine alkaloid primarily isolated from Sanguinaria canadensis and other members of the Papaveraceae family, has been documented to possess notable anti-bacterial, anti-inflammatory, and anti-neoplastic properties. Nevertheless, its potential utility as a targeted therapeutic modality for RA has yet to be systematically investigated.

Psoriasis is an autoimmune disease characterized primarily by chronic inflammation, with suboptimal clinical therapeutic outcomes. Quercetin, a bio-safe plant secondary metabolite, exerts anti-inflammatory effects by modulating multiple signaling pathways and holds promise as a therapeutic candidate for psoriasis.

Stevia rebaudiana Bertoni is a natural sweetener with reported antidiabetic properties; however, the molecular basis underlying the interactions of its major phytochemicals with key glycaemic-regulating enzymes remains insufficiently understood. The present study employed an integrated in silico workflow to evaluate the antidiabetic potential of selected steviol-derived phytochemicals against human pancreatic α-amylase and dipeptidyl peptidase-IV (DPP-IV). Methanolic leaf extracts were profiled by GC-MS, and steviol, together with the principal steviol glycosides (stevioside, rebaudioside A, and rebaudioside D), was selected for computational analyses. Pharmacokinetic properties were predicted using SwissADME, followed by molecular docking and 100 ns molecular dynamics simulations incorporating principal component analysis (PCA), free-energy landscape (FEL), dynamic cross-correlation analysis (DCCM), and hydrogen-bond analysis, together with MM-PBSA binding free energy and per-residue energy decomposition. Among the evaluated phytochemicals, steviol exhibited the most favourable predicted docking profile against α-amylase (-8.46 kcal/mol), whereas rebaudioside A showed the most favourable predicted docking profile against DPP-IV (-8.34 kcal/mol). Molecular dynamics and complementary structural analyses indicated stable conformational behaviour and provided additional insights into the dynamic and energetic characteristics of the selected protein-ligand complexes. ADME analysis further demonstrated distinct pharmacokinetic characteristics among the evaluated phytochemicals, with steviol exhibiting comparatively more favourable predicted oral drug-likeness, whereas the steviol glycosides displayed physicochemical properties that may favour gut-localised α-amylase inhibition. These findings provide computational evidence supporting the potential interactions of steviol-derived phytochemicals with α-amylase and DPP-IV. However, the results are based entirely on computational predictions and require experimental validation through in vitro enzyme inhibition assays, pharmacokinetic studies, and in vivo investigations before their therapeutic potential can be established.

Myeloproliferative neoplasms (MPNs) are driven by constitutive cytokine-receptor signaling, yet the metabolic programs associated with driver genotype and inflammatory remodeling remain incompletely defined.

Intratumoral microbiota are emerging as important ecological components of the colorectal cancer (CRC) microenvironment. However, their stage-associated patterns and coordination with host gene expression remain poorly understood. This study aimed to characterize stage-associated associations between intratumoral microbiota and the host transcriptome in CRC.

Stroke is a leading cause of long-term disability, often resulting in persistent motor impairments that reflect disruptions in large-scale brain networks. An integrated framework capturing spatiotemporal EEG dynamics would help clarify how these networks change during recovery.

Pluripotent stem cell-derived alpha cells (SC-α cells) represent a promising component of next-generation cell therapies designed to more fully recapitulate human islet function; however, heterogeneity and the presence of undesired side populations limit their functional maturity and therapeutic potential. Here, we identify the cell surface protein CD98hc (SLC3A2), that when highly expressed in precursor cells, is associated with differentiation toward a more transcriptionally and functionally mature population of human SC-α cells.