Identifying tumor antigens and immune subtypes of gastrointestinal MALT lymphoma for immunotherapy development

MALT lymphoma is an extranodal B-cell lymphoma of the marginal zone of mucosa-associated lymphoid tissue (MALT), caused by malignant transformation of B-cells in the marginal zone. In this work, we aim to explore the potential relationship between MALT lymphoma and DLBCL. Vaccines derived from messenger ribonucleic acid (mRNA) may provide satisfactory results. Despite being a promising treatment option, immunotherapy isn’t widely used in treating renal cell carcinoma, as only a few patients respond to the treatment. The Cancer Genome Atlas (TCGA) analysis revealed gene expression profiles and clinical information. Antigen-presenting cells infiltrated the immune system using TIMER tool (http://timer.cistrome.org/). GDSC (Genomics of Drug Sensitivity in Cancer) data were used to estimate drug sensitivity. Immune-related genes were associated with a better prognosis in MALT lymphoma patients and higher levels of antigen-presenting cells. There is a significant relationship between these immune subtypes and immunological checkpoints, immunogenic cell death regulators, and prognostic variables for MALT lymphoma patients. In this study, we provide a theoretical foundation for the development of mRNA vaccines and suggest that KLHL14 could potentially be used as antigens to develop mRNA vaccines for MALT lymphoma

A Novel Workflow for Early Time Transient Pressure Data Interpretation in Tight Oil Reservoirs with Physical Constraints

In this work, a novel workflow has been proposed, validated and applied to interpret the early time transient pressure data in tight oil reservoirs with physical constraints. More specifically, the theoretical model was developed to obtain the transient pressure response for a vertical well in tight oil reservoirs with consideration of pseudo threshold pressure gradient (TPG). Then, a physical constraint between the skin factor and formation permeability has been proposed based on the physical meaning of percolation theory. This physical constraint can be applied to determine the lower limit of the skin factor which can reduce the uncertainty during the interpretation process. It is found that the influence range of the skin factor and permeability may partially overlap during the interpretation process without consideration of physical constraints. Additionally, it is found that the equivalent wellbore radius is more reasonable by considering the skin factor constraints. Furthermore, the short-time asymptotic method was applied to separate the small pressure signal at the early time period and a novel type curve was proposed to better analyze the early time pressure response. Subsequently, sensitivity analyses were conducted to investigate the influence of different parameters on the new type curves. It is found that the new type curves are more dispersed and sensitive to the parameters at the early time period which can be beneficial for the early time transient pressure analysis in a tight formation. The proposed method has been validated and then extended to a field application, demonstrating that the transient pressure for a vertical well in a tight formation can be analyzed in a reasonable and accurate manner with only early time transient pressure data

A mechanistic Individual-based Model of microbial communities

Accurate predictive modelling of the growth of microbial communities requires the credible representation of the interactions of biological, chemical and mechanical processes. How-ever, although biological and chemical processes are represented in a number of Individual-based Models (IbMs) the interaction of growth and mechanics is limited. Conversely, there are mechanically sophisticated IbMs with only elementary biology and chemistry. This study focuses on addressing these limitations by developing a flexible IbM that can robustly com-bine the biological, chemical and physical processes that dictate the emergent properties of a wide range of bacterial communities. This IbM is developed by creating a microbiological adaptation of the open source Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS). This innovation should provide the basis for " bottom up " prediction of the emer-gent behaviour of entire microbial systems. In the model presented here, bacterial growth, division, decay, mechanical contact among bacterial cells, and adhesion between the bacte-ria and extracellular polymeric substances are incorporated. In addition, fluid-bacteria inter-action is implemented to simulate biofilm deformation and erosion. The model predicts that the surface morphology of biofilms becomes smoother with increased nutrient concentra-tion, which agrees well with previous literature. In addition, the results show that increased shear rate results in smoother and more compact biofilms. The model can also predict shear rate dependent biofilm deformation, erosion, streamer formation and breakup