Abstractions and performance optimisations for finite element methods

Finding numerical solutions to partial differential equations (PDEs) is an essential task in the discipline of scientific computing. In designing software tools for this task, one of the ultimate goals is to balance the needs for generality, ease to use and high performance. Domain-specific systems based on code generation techniques, such as Firedrake, attempt to address this problem with a design consisting of a hierarchy of abstractions, where the users can specify the mathematical problems via a high-level, descriptive interface, which is progressively lowered through the intermediate abstractions. Well-designed abstraction layers are essential to enable performing code transformations and optimisations robustly and efficiently, generating high-performance code without user intervention. This thesis discusses several topics on the design of the abstraction layers of Firedrake, and presents the benefit of its software architecture by providing examples of various optimising code transformations at the appropriate abstraction layers. In particular, we discuss the advantage of describing the local assembly stage of a finite element solver in an intermediate representation based on symbolic tensor algebra. We successfully lift specific loop optimisations, previously implemented by rewriting ASTs of the local assembly kernels, to this higher-level tensor language, improving the compilation speed and optimisation effectiveness. The global assembly phase involves the application of local assembly kernels on a collection of entities of an unstructured mesh. We redesign the abstraction to express the global assembly loop nests using tools and concepts based on the polyhedral model. This enables us to implement the cross-element vectorisation algorithm that delivers stable vectorisation performance on CPUs automatically. This abstraction also improves the portability of Firedrake, as we demonstrate targeting GPU devices transparently from the same software stack.Open Acces

Global synthesis of the classifications, distributions, benefits and issues of terracing

For thousands of years, humans have created different types of terraces in different sloping conditions, meant to mitigate flood risks, reduce soil erosion and conserve water. These anthropogenic landscapes can be found in tropical and subtropical rainforests, deserts, and arid and semiarid mountains across the globe. Despite the long history, the roles of and the mechanisms by which terracing improves ecosystem services (ESs) remain poorly understood. Using literature synthesis and quantitative analysis, the worldwide types, distributions, major benefits and issues of terracing are presented in this review. A key terracing indicator, defined as the ratio of different ESs under terraced and non-terraced slopes (δ), was used to quantify the role of terracing in providing ESs. Our results indicated that ESs provided by terracingwas generally positive because themean values of δ were mostly greater than one. The most prominent role of terracing was found in erosion control (11.46 ± 2.34), followed by runoff reduction (2.60 ± 1.79), biomass accumulation (1.94 ± 0.59), soil water recharge (1.20±0.23), and nutrient enhancement (1.20±0.48). Terracing, to a lesser extent, could also enhance the survival rates of plant seedlings, promote ecosystem restoration, and increase crop yields.While slopes experiencing severe human disturbance (e.g., overgrazing and deforestation) can generally become more stable after terracing, negative effects of terracing may occur in poorly-designed or poorly-managed terraces. Among the reasons are the lack of environmental legislation, changes in traditional concepts and lifestyles of local people, as well as price decreases for agricultural products. All of these can accelerate terrace abandonment and degradation. In light of these findings, possible solutions regarding socio-economic changes and techniques to improve already degraded terraces are discussed

E2F1 Suppresses Oxidative Metabolism and Endothelial Differentiation of Bone Marrow Progenitor Cells

RATIONALE: The majority of current cardiovascular cell therapy trials use bone marrow progenitor cells (BM PCs) and achieve only modest efficacy; the limited potential of these cells to differentiate into endothelial-lineage cells is one of the major barriers to the success of this promising therapy. We have previously reported that the E2F transcription factor 1 (E2F1) is a repressor of revascularization after ischemic injury. OBJECTIVE: We sought to define the role of E2F1 in the regulation of BM PC function. METHODS AND RESULTS: Ablation of E2F1 (E2F1 deficient) in mouse BM PCs increases oxidative metabolism and reduces lactate production, resulting in enhanced endothelial differentiation. The metabolic switch in E2F1-deficient BM PCs is mediated by a reduction in the expression of pyruvate dehydrogenase kinase 4 and pyruvate dehydrogenase kinase 2; overexpression of pyruvate dehydrogenase kinase 4 reverses the enhancement of oxidative metabolism and endothelial differentiation. Deletion of E2F1 in the BM increases the amount of PC-derived endothelial cells in the ischemic myocardium, enhances vascular growth, reduces infarct size, and improves cardiac function after myocardial infarction. CONCLUSION: Our results suggest a novel mechanism by which E2F1 mediates the metabolic control of BM PC differentiation, and strategies that inhibit E2F1 or enhance oxidative metabolism in BM PCs may improve the effectiveness of cell therapy

Identification of a cellular senescence-related-lncRNA (SRlncRNA) signature to predict the overall survival of glioma patients and the tumor immune microenvironment

Background: Gliomas are brain tumors that arise from glial cells, and they are the most common primary intracranial tumors with a poor prognosis. Cellular senescence plays a critical role in cancer, especially in glioma. In this study, we constructed a senescence-related lncRNA (SRlncRNA) signature to assess the prognosis of glioma.Methods: The Cancer Genome Atlas was used to collect SRlncRNA transcriptome profiles and clinical data about glioma. Patients were randomized to training, testing, and whole cohorts. LASSO and Cox regression analyses were employed to construct the SRlncRNA signature, and Kaplan–Meier (K-M) analysis was performed to determine each cohort’s survival. Receiver operating characteristic (ROC) curves were applied to verify the accuracy of this signature. Gene set enrichment analysis was used to visualize functional enrichment (GSEA). The CIBERSORT algorithm, ESTIMATE and TIMER databases were utilized to evaluate the differences in the infiltration of 22 types of immune cells and their association with the signature. RT–qPCR and IHC were used to identify the consistency of the signature in tumor tissue.Results: An SRlncRNA signature consisting of six long non-coding RNAs (lncRNAs) was constructed, and patients were divided into high-risk and low-risk groups by the median of their riskscore. The KM analysis showed that the high-risk group had worse overall survival, and the ROC curve confirmed that the riskscore had more accurate predictive power. A multivariate Cox analysis and its scatter plot with clinical characteristics confirmed the riskscore as an independent risk factor for overall survival. GSEA showed that the GO and KEGG pathways were mainly enriched in the immune response to tumor cells, p53 signaling pathway, mTOR signaling pathway, and Wnt signaling pathway. Further validation also yielded significant differences in the risk signature in terms of immune cell infiltration, which may be closely related to prognostic differences, and qRT–PCR and IHC confirmed the consistency of the expression differences in the major lncRNAs with those in the prediction model.Conclusion Our findings indicated that the SRlncRNA signature might be used as a predictive biomarker and that there is a link between it and immune infiltration. This discovery is consistent with the present categorization system and may open new avenues for research and personalized therapy

Global synthesis of the classifications, distributions, benefits and issues of terracing

For thousands of years, humans have created different types of terraces in different sloping conditions, meant to mitigate flood risks, reduce soil erosion and conserve water. These anthropogenic landscapes can be found in tropical and subtropical rainforests, deserts, and arid and semiarid mountains across the globe. Despite the long history, the roles of and the mechanisms by which terracing improves ecosystem services (ESs) remain poorly understood. Using literature synthesis and quantitative analysis, the worldwide types, distributions, major benefits and issues of terracing are presented in this review. A key terracing indicator, defined as the ratio of different ESs under terraced and non-terraced slopes (δ), was used to quantify the role of terracing in providing ESs. Our results indicated that ESs provided by terracingwas generally positive because themean values of δ were mostly greater than one. The most prominent role of terracing was found in erosion control (11.46 ± 2.34), followed by runoff reduction (2.60 ± 1.79), biomass accumulation (1.94 ± 0.59), soil water recharge (1.20±0.23), and nutrient enhancement (1.20±0.48). Terracing, to a lesser extent, could also enhance the survival rates of plant seedlings, promote ecosystem restoration, and increase crop yields.While slopes experiencing severe human disturbance (e.g., overgrazing and deforestation) can generally become more stable after terracing, negative effects of terracing may occur in poorly-designed or poorly-managed terraces. Among the reasons are the lack of environmental legislation, changes in traditional concepts and lifestyles of local people, as well as price decreases for agricultural products. All of these can accelerate terrace abandonment and degradation. In light of these findings, possible solutions regarding socio-economic changes and techniques to improve already degraded terraces are discussed

Suppression of Tumor Energy Supply by Liposomal Nanoparticle-Mediated Inhibition of Aerobic Glycolysis

Aerobic glycolysis enables cancer cells to rapidly take up nutrients (e.g., nucleotides, amino acids, and lipids) and incorporate them into the biomass needed to produce a new cell. In contrast to existing chemotherapy/radiotherapy strategies, inhibiting aerobic glycolysis to limit the adenosine 5′-triphosphate (ATP) yield is a highly efficient approach for suppressing tumor cell proliferation. However, most, if not all, current inhibitors of aerobic glycolysis cause significant adverse effects because of their nonspecific delivery and distribution to nondiseased organs, low bioavailability, and a narrow therapeutic window. New strategies to enhance the biosafety and efficacy of these inhibitors are needed for moving them into clinical applications. To address this need, we developed a liposomal nanocarrier functionalized with a well-validated tumor-targeting peptide to specifically deliver the aerobic glycolysis inhibitor 3-bromopyruvate (3-BP) into the tumor tissue. The nanoparticles effectively targeted tumors after systemic administration into tumor-bearing mice and suppressed tumor growth by locally releasing 3-BP to inhibit the ATP production of the tumor cells. No overt side effects were observed in the major organs. This report demonstrates the potential utility of the nanoparticle-enabled delivery of an aerobic glycolysis inhibitor as an anticancer therapeutic agent

Single cell atlas for 11 non-model mammals, reptiles and birds.

The availability of viral entry factors is a prerequisite for the cross-species transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Large-scale single-cell screening of animal cells could reveal the expression patterns of viral entry genes in different hosts. However, such exploration for SARS-CoV-2 remains limited. Here, we perform single-nucleus RNA sequencing for 11 non-model species, including pets (cat, dog, hamster, and lizard), livestock (goat and rabbit), poultry (duck and pigeon), and wildlife (pangolin, tiger, and deer), and investigated the co-expression of ACE2 and TMPRSS2. Furthermore, cross-species analysis of the lung cell atlas of the studied mammals, reptiles, and birds reveals core developmental programs, critical connectomes, and conserved regulatory circuits among these evolutionarily distant species. Overall, our work provides a compendium of gene expression profiles for non-model animals, which could be employed to identify potential SARS-CoV-2 target cells and putative zoonotic reservoirs