Genetic polymorphisms in MDR1 and CYP3A4 genes in Asians and the influence of MDR1 haplotypes on cyclosporin disposition in heart transplant recipients.

Intestinal cytochrome P450 3A4 (CYP3A4) and P-glycoprotein (P-gp) both play a vital role in the metabolism of oral cyclosporine (CsA). We investigated the genetic polymorphisms in CYP3A4(promoter region and exons 5, 7 and 9) and MDR1 (exons 12, 21 and 26) genes and the impact of these polymorphisms on the pharmacokinetics of oral CsA in stable heart transplant patients (n = 14). CYP3A4 polymorphisms were rare in the Asian population and transplant patients. Haplotype analysis revealed 12 haplotypes in the Chinese, eight in the Malays and 10 in the Indians. T-T-T was the most common haplotype in all ethnic groups. The frequency of the homozygous mutant genotype at all three loci (TT-TT-TT) was highest in the Indians (31%) compared to 19% and 15% in the Chinese and Malays, respectively. In heart transplant patients, CsA exposure (AUC(0-4 h), AUC(0-12 h) and C(max)) was high in patients with the T-T-T haplotypes compared to those with C-G-C haplotypes. These findings suggest that haplotypes rather than genotypes influence CsA disposition in transplant patients

Knowledge Graph Reasoning over Entities and Numerical Values

A complex logic query in a knowledge graph refers to a query expressed in logic form that conveys a complex meaning, such as where did the Canadian Turing award winner graduate from? Knowledge graph reasoning-based applications, such as dialogue systems and interactive search engines, rely on the ability to answer complex logic queries as a fundamental task. In most knowledge graphs, edges are typically used to either describe the relationships between entities or their associated attribute values. An attribute value can be in categorical or numerical format, such as dates, years, sizes, etc. However, existing complex query answering (CQA) methods simply treat numerical values in the same way as they treat entities. This can lead to difficulties in answering certain queries, such as which Australian Pulitzer award winner is born before 1927, and which drug is a pain reliever and has fewer side effects than Paracetamol. In this work, inspired by the recent advances in numerical encoding and knowledge graph reasoning, we propose numerical complex query answering. In this task, we introduce new numerical variables and operations to describe queries involving numerical attribute values. To address the difference between entities and numerical values, we also propose the framework of Number Reasoning Network (NRN) for alternatively encoding entities and numerical values into separate encoding structures. During the numerical encoding process, NRN employs a parameterized density function to encode the distribution of numerical values. During the entity encoding process, NRN uses established query encoding methods for the original CQA problem. Experimental results show that NRN consistently improves various query encoding methods on three different knowledge graphs and achieves state-of-the-art results

Spatial variation of perceived equity and its determinants in a gateway community of Giant Panda National Park, China

Unidad de excelencia María de Maeztu CEX2019-000940-MSocial equity is essential in the governance of protected areas (PAs), as ignoring such consideration can lead to resistance and jeopardize conservation objectives. However, more research is required to understand the spatial heterogeneity of perceived social equity and its underlying spatial factors. Using a survey of 361 respondents, we presented spatial distribution patterns of perceived equity by kernel density estimation (KDE) in Giant Panda National Park, China. The regression analysis showed that local residents who live closer to the PA boundary are more likely to develop negative responses and those who with easy access to tourism spots have more positive procedural and distributional perceptions. Notably, the proximity to the PA authority decreases locals' perceptions of fairness in all aspects, which is potentially due to the opaque participative channels provided by the PA authority. We argue that those spatial differentials in fairness perceptions are driven by the intrinsic discrepancy of biodiversity protection requirements and the unevenly distributed consequences of management policies. Key steps to advance social equity considerations include multi-industry guidance, extending participative channels, and co-producing better compensation plans. Herein, this study appeals to a greater focus on the spatial aspect of social equity issues in PAs

Graph Reasoning for Question Answering with Triplet Retrieval

Answering complex questions often requires reasoning over knowledge graphs (KGs). State-of-the-art methods often utilize entities in questions to retrieve local subgraphs, which are then fed into KG encoder, e.g. graph neural networks (GNNs), to model their local structures and integrated into language models for question answering. However, this paradigm constrains retrieved knowledge in local subgraphs and discards more diverse triplets buried in KGs that are disconnected but useful for question answering. In this paper, we propose a simple yet effective method to first retrieve the most relevant triplets from KGs and then rerank them, which are then concatenated with questions to be fed into language models. Extensive results on both CommonsenseQA and OpenbookQA datasets show that our method can outperform state-of-the-art up to 4.6% absolute accuracy.Comment: Findings of ACL 202