Lymph Node Stromal Cell Subsets

The spatiotemporal regulation of immune responses in the lymph node (LN) depends on its sophisticated tissue architecture, consisting of several subcompartments supported by distinct fibroblastic stromal cells (FSCs). However, the intricate details of stromal structures and associated FSC subsets are not fully understood. Using several gene reporter mice, we sought to discover unrecognized stromal structures and FSCs in the LN. The four previously identified FSC subsets in the cortex are clearly distinguished by the expression pattern of reporters including PDGFRb, CCL21-ser, and CXCL12. Herein, we identified a unique FSC subset expressing both CCL21-ser and CXCL12 in the deep cortex periphery (DCP) that is characterized by preferential B cell localization. This subset was clearly different fromCXCL12highLepRhigh FSCs in themedullary cord, which harbors plasma cells. B cell localization in the DCP was controlled chiefly by CCL21-ser and, to a lesser extent, CXCL12. Moreover, the optimal development of the DCP as well as medulla requires B cells. Together, our findings suggest the presence of a unique microenvironment in the cortex-medulla boundary and offer an advanced view of the multi-layered stromal framework constructed by distinct FSC subsets in the LN

A Distinct Subset of Fibroblastic Stromal Cells Constitutes the Cortex-Medulla Boundary Subcompartment of the Lymph Node

The spatiotemporal regulation of immune responses in the lymph node (LN) depends on its sophisticated tissue architecture, consisting of several subcompartments supported by distinct fibroblastic stromal cells (FSCs). However, the intricate details of stromal structures and associated FSC subsets are not fully understood. Using several gene reporter mice, we sought to discover unrecognized stromal structures and FSCs in the LN. The four previously identified FSC subsets in the cortex are clearly distinguished by the expression pattern of reporters including PDGFRβ, CCL21-ser, and CXCL12. Herein, we identified a unique FSC subset expressing both CCL21-ser and CXCL12 in the deep cortex periphery (DCP) that is characterized by preferential B cell localization. This subset was clearly different from CXCL12highLepRhigh FSCs in the medullary cord, which harbors plasma cells. B cell localization in the DCP was controlled chiefly by CCL21-ser and, to a lesser extent, CXCL12. Moreover, the optimal development of the DCP as well as medulla requires B cells. Together, our findings suggest the presence of a unique microenvironment in the cortex-medulla boundary and offer an advanced view of the multi-layered stromal framework constructed by distinct FSC subsets in the LN

RNA biomarkers in colorectal cancer

Colorectal cancer (CRC) develops and progresses through a systematic selection for (epi) genetic alterations that drive the transformation from normal colon epithelium to adenocarcinoma. These changes affect both noncoding RNAs and mRNAs and so define the clinical behaviour of cancer cells within a distinctive host genetic and environmental context. Although earlier diagnosis and more effective treatment modalities have decreased mortality from CRC, prognostic stratification and adjuvant therapy selection after surgery remain dependent on broad descriptive classifications, opportune histological markers of poor prognosis and chemotherapy efficacy data derived from diverse CRC populations. Crucially, there is significant inter- and intra-individual variability in response to, and tolerance of, chemotherapy treatments. These limitations explain the small clinical benefit of new agents studied in contemporary phase III trials. Molecular assays have the potential to address these constraints and there has been intense interest in the identification of clinically relevant molecular biomarkers. These must be easy to obtain and quantify and ideally represent steps in well-understood carcinogenic pathways or host-response mechanisms. Although some biomarkers can provide broad prognostic information based on CRC subtype (e.g. MSI status) or can somewhat predict response to targeted therapies (e.g. KRAS), no RNA-based biomarkers have entered routine clinical practice. This is due, in part, to the genetic heterogeneity of both patients and CRC. In addition, serious underlying issues with regards to study design, poor technical protocols, inadequate quality controls and inappropriate data analysis prevent successful translation of research results. Consequently, the identification of clinically relevant panels of biomarkers will depend not just on further advances in our understanding of CRC biology, but will need to be coupled with appropriate study designs and more suitable, standardised and transparent techniques

BLOOM: A 176B-Parameter Open-Access Multilingual Language Model

Large language models (LLMs) have been shown to be able to perform new tasks based on a few demonstrations or natural language instructions. While these capabilities have led to widespread adoption, most LLMs are developed by resource-rich organizations and are frequently kept from the public. As a step towards democratizing this powerful technology, we present BLOOM, a 176B-parameter open-access language model designed and built thanks to a collaboration of hundreds of researchers. BLOOM is a decoder-only Transformer language model that was trained on the ROOTS corpus, a dataset comprising hundreds of sources in 46 natural and 13 programming languages (59 in total). We find that BLOOM achieves competitive performance on a wide variety of benchmarks, with stronger results after undergoing multitask prompted finetuning. To facilitate future research and applications using LLMs, we publicly release our models and code under the Responsible AI License