Strain specific differences in vitamin D3 response: impact on gut homeostasis.

Vitamin D3 regulates a variety of biological processes irrespective of its well-known importance for calcium metabolism. Epidemiological and animal studies indicate a role in immune regulation, intestinal barrier function and microbiome diversity. Here, we analyzed the impact of different vitamin D3- containing diets on C57BL/6 and BALB/c mice, with a particular focus on gut homeostasis and also investigated effects on immune cells .

Intestinal IgA-positive plasma cells are highly sensitive indicators of alloreaction early after allogeneic transplantation and associate with both graft-versus-host disease and relapse-related mortality.

Intestinal immunoglobulin A (IgA) is strongly involved in microbiota homeostasis. Since microbiota disruption is a major risk factor of acute graft-versus-host disease (GvHD), we addressed the kinetics of intestinal IgA-positive (IgA+) plasma cells by immunohistology in a series of 430 intestinal biopsies obtained at a median of 1,5 months after allogeneic stem cell transplantation (allo-SCT) from 115 patients (pts) at our center. IgA+ plasma cells were located in the subepithelial lamina propria and suppressed in the presence of histological aGvHD (GvHD Lerner stage 0: 131+/-8 IgA+ plasma cells/mm2; stage 1-2: 108+/-8 IgA+ plasma cells/mm2; stage 3-4: 89+/-16 IgA+ plasma cells/mm2; P=0.

Prognostic impact of variant histologies in urothelial bladder cancer treated with radical cystectomy.

Objectives: To evaluate variant histologies (VHs) for disease-specific survival (DSS) in patients with invasive urothelial bladder cancer (BCa) undergoing radical cystectomy (RC).

Materials And Methods: We analysed a multi-institutional cohort of 1082 patients treated with upfront RC for cT1-4aN0M0 urothelial BCa at eight centres. Univariable and multivariable Cox' regression analyses were used to assess the effect of different VHs on DSS in overall cohort and three stage-based analyses.

GenSLMs: Genome-scale language models reveal SARS-CoV-2 evolutionary dynamics.

We seek to transform how new and emergent variants of pandemic-causing viruses, specifically SARS-CoV-2, are identified and classified. By adapting large language models (LLMs) for genomic data, we build genome-scale language models (GenSLMs) which can learn the evolutionary landscape of SARS-CoV-2 genomes. By pre-training on over 110 million prokaryotic gene sequences and fine-tuning a SARS-CoV-2-specific model on 1.