Curcumin is a poorly water-soluble drug that is used for the treatment of inflammations, tumors, wound healing antioxidant and other diseases. In the current manuscript, it is successfully formulated into proniosome gels. The proniosomes are readily hydrated into niosomal formulations using warm water. Proniosomes were prepared using nonionic surfactants (tween 80, span 60) either solely or in combinations with cholesterol. The produced niosomal formulations were homogenous in size with vesicular sizes >343 and <1800 nm. The encapsulation efficiency percentage "EE%" of curcumin in niosomal formulations was different according to niosomal composition. It increased up to 99.74% in formulations of tween 80/Chol of 200 μmole/mL lipid concentration. Span 60/chol niosomes showed decreased curcumin EE%. Niosomal formulations showed increased SSTF and PC with enhancement ratios of more than 20-fold compared with curcumin suspension form. Kinetically, niosomes fitted to the Korsemeyer-Peppas model with non-Fickian transport according to their calculated n-values where curcumin suspension form showed Korsemeyer-Peppas kinetics with Fickian transport. Niosomal formulations deposited higher curcumin amounts in the skin compared with the suspension form. The best niosomal formulation (F9) was used for niosomal gel and emulgel fabrication. Finally, the anti-inflammatory activity of curcumin in various formulations was evaluated using a rat hind paw edema method and the % of swelling was 17.5% following 24 h in group treated with curcumin niosomal emulgel. In conclusion, this study suggests that the developed niosomal emulgel could significantly enhance the anti-inflammatory effect of curcumin and be an efficient carrier for the transdermal delivery of the drug.

Direct cell programming via overexpression of transcription factors (TFs) aims to control cell fate with the degree of precision needed for clinical applications. However, the regulatory steps involved in successful terminal cell fate programming remain obscure. We have investigated the underlying mechanisms by looking at gene expression, chromatin states, and TF binding during the uniquely efficient Ngn2, Isl1, and Lhx3 motor neuron programming pathway. Our analysis reveals a highly dynamic process in which Ngn2 and the Isl1/Lhx3 pair initially engage distinct regulatory regions. Subsequently, Isl1/Lhx3 binding shifts from one set of targets to another, controlling regulatory region activity and gene expression as cell differentiation progresses. Binding of Isl1/Lhx3 to later motor neuron enhancers depends on the Ebf and Onecut TFs, which are induced by Ngn2 during the programming process. Thus, motor neuron programming is the product of two initially independent transcriptional modules that converge with a feedforward transcriptional logic.

Divergent transcription, in which reverse-oriented transcripts occur upstream of eukaryotic promoters in regions devoid of annotated genes, has been suggested to be a general property of active promoters. Here we show that the human basal RNA polymerase II transcriptional machinery and core promoter are inherently unidirectional and that reverse-oriented transcripts originate from their own cognate reverse-directed core promoters. In vitro transcription analysis and mapping of nascent transcripts in HeLa cells revealed that sequences at reverse start sites are similar to those of their forward counterparts. The use of DNase I accessibility to define proximal promoter borders revealed that about half of promoters are unidirectional and that unidirectional promoters are depleted at their upstream edges of reverse core promoter sequences and their associated chromatin features. Divergent transcription is thus not an inherent property of the transcription process but rather the consequence of the presence of both forward- and reverse-directed core promoters.

The prediction of transcription factor (TF) activities from the gene expression of their targets (i.e., TF regulon) is becoming a widely used approach to characterize the functional status of transcriptional regulatory circuits. Several strategies and data sets have been proposed to link the target genes likely regulated by a TF, each one providing a different level of evidence. The most established ones are (1) manually curated repositories, (2) interactions derived from ChIP-seq binding data, (3) in silico prediction of TF binding on gene promoters, and (4) reverse-engineered regulons from large gene expression data sets. However, it is not known how these different sources of regulons affect the TF activity estimations and, thereby, downstream analysis and interpretation. Here we compared the accuracy and biases of these strategies to define human TF regulons by means of their ability to predict changes in TF activities in three reference benchmark data sets. We assembled a collection of TF-target interactions for 1541 human TFs and evaluated how different molecular and regulatory properties of the TFs, such as the DNA-binding domain, specificities, or mode of interaction with the chromatin, affect the predictions of TF activity. We assessed their coverage and found little overlap on the regulons derived from each strategy and better performance by literature-curated information followed by ChIP-seq data. We provide an integrated resource of all TF-target interactions derived through these strategies, with confidence scores, as a resource for enhanced prediction of TF activities.

Kidney fibrosis is the hallmark of chronic kidney disease progression; however, at present no antifibrotic therapies exist1-3. The origin, functional heterogeneity and regulation of scar-forming cells that occur during human kidney fibrosis remain poorly understood1,2,4. Here, using single-cell RNA sequencing, we profiled the transcriptomes of cells from the proximal and non-proximal tubules of healthy and fibrotic human kidneys to map the entire human kidney. This analysis enabled us to map all matrix-producing cells at high resolution, and to identify distinct subpopulations of pericytes and fibroblasts as the main cellular sources of scar-forming myofibroblasts during human kidney fibrosis. We used genetic fate-tracing, time-course single-cell RNA sequencing and ATAC-seq (assay for transposase-accessible chromatin using sequencing) experiments in mice, and spatial transcriptomics in human kidney fibrosis, to shed light on the cellular origins and differentiation of human kidney myofibroblasts and their precursors at high resolution. Finally, we used this strategy to detect potential therapeutic targets, and identified NKD2 as a myofibroblast-specific target in human kidney fibrosis.

The development of single-cell RNA sequencing (scRNA-seq) technologies has greatly contributed to deciphering the tumor microenvironment (TME). An enormous amount of independent scRNA-seq studies have been published representing a valuable resource that provides opportunities for meta-analysis studies. However, the massive amount of biological information, the marked heterogeneity and variability between studies, and the technical challenges in processing heterogeneous datasets create major bottlenecks for the full exploitation of scRNA-seq data. We have developed IMMUcan scDB (https://immucanscdb.vital-it.ch), a fully integrated scRNA-seq database exclusively dedicated to human cancer and accessible to nonspecialists. IMMUcan scDB encompasses 144 datasets on 56 different cancer types, annotated in 50 fields containing precise clinical, technological, and biological information. A data processing pipeline was developed and organized in four steps: (i) data collection; (ii) data processing (quality control and sample integration); (iii) supervised cell annotation with a cell ontology classifier of the TME; and (iv) interface to analyze TME in a cancer type-specific or global manner. This framework was used to explore datasets across tumor locations in a gene-centric (CXCL13) and cell-centric (B cells) manner as well as to conduct meta-analysis studies such as ranking immune cell types and genes correlated to malignant transformation. This integrated, freely accessible, and user-friendly resource represents an unprecedented level of detailed annotation, offering vast possibilities for downstream exploitation of human cancer scRNA-seq data for discovery and validation studies.

Divergent transcription from promoters and enhancers is pervasive in many species, but it remains unclear if it is a general feature of all eukaryotic cis regulatory elements. To address this, here we define cis regulatory elements in C. elegans, D. melanogaster and H. sapiens and investigate the determinants of their transcription directionality. In all three species, we find that divergent transcription is initiated from two separate core promoter sequences and promoter regions display competition between histone modifications on the + 1 and -1 nucleosomes. In contrast, promoter directionality, sequence composition surrounding promoters, and positional enrichment of chromatin states, are different across species. Integrative models of H3K4me3 levels and core promoter sequence are highly predictive of promoter and enhancer directionality and support two directional classes, skewed and balanced. The relative importance of features to these models are clearly distinct for promoters and enhancers. Differences in regulatory architecture within and between metazoans are therefore abundant, arguing against a unified eukaryotic model.

To develop effective therapies and identify novel early biomarkers for chronic kidney disease, an understanding of the molecular mechanisms orchestrating it is essential. We here set out to understand how differences in chronic kidney disease (CKD) origin are reflected in gene expression. To this end, we integrated publicly available human glomerular microarray gene expression data for 9 kidney disease entities that account for most of CKD worldwide. Our primary goal was to demonstrate the possibilities and potential on data analysis and integration to the nephrology community.