A bioinspired supramolecular nanoprodrug for precision therapy of B-cell non-Hodgkin's lymphoma.

Fludarabine (FA) is still considered as a first-line chemotherapy drug for hematological tumors related to B lymphocytes. However, it is worth noting that the non-specific distribution and non-different cytotoxicity of FA may lead to irreversible consequences such as central nervous system damage such as blindness, coma, and even death. Therefore, it is very important to develop a system to targeting delivery FA. In preliminary studies, it was found that B lymphoma cells would specific highly expressing the sialic acid-binding immunoglobulin-like lectin 2 (known as CD22). Inspired by the specific recognition of sialic acid residues and CD22, we have developed a supramolecular prodrug based on polysialic acid, an endogenous biomacromolecule, achieving targeted-therapy of B-cell non-Hodgkin's lymphoma (B-NHL). Specifically, the prepared hydrophobic reactive oxygen species-responsive FA dimeric prodrug (F2A) interacts with the TPSA, which polysialic acid were modified by the thymidine derivatives, through non-covalent intermolecular interactions similar to "Watson-Crick" base pairing, resulting in the formation of nanoscale supramolecular prodrug (F@TPSA). Cell experiments have confirmed that F@TPSA can be endocytosed by CD22+ B lymphoma cells including Raji and Ramos cells, and there is a significant difference of endocytosis in other leukocytes. Furthermore, in B-NHL mouse model, compared with FA, F@TPSA is determined to have a stronger tumor targeting and inhibitory effect. More importantly, the distribution of F@TPSA in vivo tends to be enriched in lymphoma tissue rather than nonspecific, thus reducing the leukopenia of FA. The targeted delivery system based on PSA provides a new prodrug modification strategy for targeted treatment of B-NHL.

Selaginellin derivatives from Selaginella tamariscina and evaluation for anti-breast cancer activity.

A phytochemical investigation of Selaginella tamariscina led to the isolation of 17 selaginellin derivatives. Their inhibitory activities against breast cancer cells were screened, and preliminary structure-activity relationships were also established. Among them, dimeric selaginellin 17 showed potential activity against MDA-MB-231 cells with an IC50 value of 3.2 ± 0.1 µM, corresponding to 4-fold higher potency than the reference compound 5-FU (IC50 14.8 ± 0.2 µM). Mechanistic studies indicated that 17 could cause G2/M phase arrest in MDA-MB-231 cells and induce apoptosis accompanied by increased ROS levels.

A multi-omic single-cell landscape of cellular diversification in the developing human cerebral cortex.

The vast neuronal diversity in the human neocortex is vital for high-order brain functions, necessitating elucidation of the regulatory mechanisms underlying such unparalleled diversity. However, recent studies have yet to comprehensively reveal the diversity of neurons and the molecular logic of neocortical origin in humans at single-cell resolution through profiling transcriptomic or epigenomic landscapes, owing to the application of unimodal data alone to depict exceedingly heterogeneous populations of neurons. In this study, we generated a comprehensive compendium of the developing human neocortex by simultaneously profiling gene expression and open chromatin from the same cell. We computationally reconstructed the differentiation trajectories of excitatory projection neurons of cortical origin and inferred the regulatory logic governing lineage bifurcation decisions for neuronal diversification. We demonstrated that neuronal diversity arises from progenitor cell lineage specificity and postmitotic differentiation at distinct stages. Our data paves the way for understanding the primarily coordinated regulatory logic for neuronal diversification in the neocortex.

Pig-eRNAdb: a comprehensive enhancer and eRNA dataset of pigs.

Enhancers and the enhancer RNAs (eRNAs) have been strongly implicated in regulations of transcriptions. Based the multi-omics data (ATAC-seq, ChIP-seq and RNA-seq) from public databases, Pig-eRNAdb is a dataset that comprehensively integrates enhancers and eRNAs for pigs using the machine learning strategy, which incorporates 82,399 enhancers and 37,803 eRNAs from 607 samples across 15 tissues of pigs. This user-friendly dataset covers a comprehensive depth of enhancers and eRNAs annotation for pigs. The coordinates of enhancers and the expression patterns of eRNAs are downloadable. Besides, thousands of regulators on eRNAs, the target genes of eRNAs, the tissue-specific eRNAs, and the housekeeping eRNAs are also accessible as well as the sequence similarity of eRNAs with humans. Moreover, the tissue-specific eRNA-trait associations encompass 652 traits are also provided. It will crucially facilitate investigations on enhancers and eRNAs with Pig-eRNAdb as a reference dataset in pigs.