A new demand function graph: Analysis of retailer-to-individual customer product supply strategies under a non-essential demand pattern.

The core objective of a successful product supply strategy is to determine the mechanism through which consumers' psychological effects influence customer demand. As stated in the theory of supply and demand, a higher level of dynamic equilibrium should be formed in which demand drives supply and supply creates demand. There is a lack of systematic research in the literature on the identification of consumer goods demand attributes and the formation of influencing factors in consumer goods supply chains. In this paper, we use the literature on demand functions and product pricing functions to establish three mathematical models to study the factors that influence retailers in designing and planning product supply strategies for different customers under nonessential demand patterns and to solve the profit maximization problem. The results of numerical examples validate the validity of the model. The research results can help retailers develop different supply strategies according to different types of customers and different demand patterns, thereby improving business performance. The theoretical contribution of this study is the construction of value ranges and a demand function diagram for identifying consumer product demand attributes.

Transcription factor 12-mediated self-feedback regulatory mechanism is required in DUX4 fusion leukaemia.

BACKGROUND: IGH::DUX4 is frequently observed in 4% B-cell acute lymphoblastic leukaemia patients. Regarding the IGH::DUX4-driven transactivation and alternative splicing, which are the main reasons behind this acute leukaemia outbreak, it remains unclear how transcriptional cofactors contribute to this oncogenic process. Further investigation is required to elucidate their specific role in leukaemogenesis. METHODS: In order to investigate the cofactors of IGH::DUX4, integrated mining of Chromatin immunoprecipitation (ChIP)-sequencing and RNA-sequencing of leukaemia cells and patient samples were conducted. Furthermore, to elucidate the synergistic interaction between transcription factor 12 (TCF12) and IGH::DUX4, knockdown and knockout experiment, mammalian two-hybridisation assay, co-immunoprecipitation and in situ proximity ligation assays were carried out. Additionally, to further investigate the direct interaction between TCF12 and IGH::DUX4, AI-based structural simulations were utilised. Finally, to validate the synergistic role of TCF12 in promoting IGH::DUX4 leukaemia, cell proliferation, apoptosis and drug sensitivity experiments were performed. RESULTS: In this study, we observed that the IGH::DUX4 target gene TCF12 might be an important cofactor/helper for this oncogenic driver. The co-expression of IGH::DUX4 and TCF12 resulted in enhanced DUX4-driven transactivation. Supportively, knockdown and knockout of TCF12 significantly reduced expression of IGH::DUX4-driven target genes in leukaemia REH (a precursor B-cell leukaemia cell line) and NALM-6 cells (a precursor B-cell leukaemia cell line). Consistently, in TCF12 knockout cells, the expression of structure-based TCF12 mutant, but not wild-type TCF12, failed to restore the TCF12-IGH::DUX4 crosstalk and the synergistic transactivation. More importantly, the breakdown in TCF12-IGH::DUX4 cooperation impaired IGH::DUX4-driven leukaemia cell survival, caused sensitivity to the chemotherapy. CONCLUSIONS: Altogether, these results helped to define a previously unrecognised TCF12-mediated positive self-feedback regulatory mechanism in IGH::DUX4 leukaemia, which holds the potential to function as a pivotal drug target for the management of this particular form of leukaemia. HIGHLIGHTS: Transcription factor 12 (TCF12) is a new novel cofactor in IGH::DUX4 transcriptional complexes/machinery. TCF12 mediates a positive self-feedback regulatory mechanism in IGH::DUX4-driven oncogenic transaction. IGH::DUX4-TCF12 structure/cooperation might represent a potent target/direction in future drug design against B-cell acute lymphoblastic leukaemia.

A comprehensive benchmarking of differential splicing tools for RNA-seq analysis at the event level.

RNA alternative splicing, a post-transcriptional stage in eukaryotes, is crucial in cellular homeostasis and disease processes. Due to the rapid development of the next-generation sequencing (NGS) technology and the flood of NGS data, the detection of differential splicing from RNA-seq data has become mainstream. A range of bioinformatic tools has been developed. However, until now, an independent and comprehensive comparison of available algorithms/tools at the event level is still lacking. Here, 21 different tools are subjected to systematic evaluation, based on simulated RNA-seq data where exact differential splicing events are introduced. We observe immense discrepancies among these tools. SUPPA, DARTS, rMATS and LeafCutter outperforme other event-based tools. We also examine the abilities of the tools to identify novel splicing events, which shows that most event-based tools are unsuitable for discovering novel splice sites. To improve the overall performance, we present two methodological approaches i.e. low-expression transcript filtering and tool-pair combination. Finally, a new protocol of selecting tools to perform differential splicing analysis for different analytical tasks (e.g. precision and recall rate) is proposed. Under this protocol, we analyze the distinct splicing landscape in the DUX4/IGH subgroup of B-cell acute lymphoblastic leukemia and uncover the differential splicing of TCF12. All codes needed to reproduce the results are available at https://github.com/mhjiang97/Benchmarking_DS.