LoGo-GR: A Local to Global Graphical Reasoning Framework for Extracting Structured Information From Biomedical Literature.

In the biomedical literature, entities are often distributed within multiple sentences and exhibit complex interactions. As the volume of literature has increased dramatically, it has become impractical to manually extract and maintain biomedical knowledge, which would entail enormous costs. Fortunately, document-level relation extraction can capture associations between entities from complex text, helping researchers efficiently mine structured knowledge from the vast medical literature. However, how to effectively synthesize rich global information from context and accurately capture local dependencies between entities is still a great challenge. In this paper, we propose a Local to Global Graphical Reasoning framework (LoGo-GR) based on a novel Biased Graph Attention mechanism (B-GAT). It learns global context feature and information of local relation path dependencies from mention-level interaction graph and entity-level path graph respectively, and collaborates with global and local reasoning to capture complex interactions between entities from document-level text. In particular, B-GAT integrates structural dependencies into the standard graph attention mechanism (GAT) as attention biases to adaptively guide information aggregation in graphical reasoning. We evaluate our method on three publicly biomedical document-level datasets: Drug-Mutation Interaction (DV), Chemical-induced Disease (CDR), and Gene-Disease Association (GDA). LoGo-GR has advanced and stable performance compared to other state-of-the-art methods (it achieves state-of-the-art performance with 96.14%-97.39% F1 on DV dataset, advanced performance with 68.89% F1 and 84.22% F1 on CDR and GDA datasets, respectively). In addition, LoGo-GR also shows advanced performance on general-domain document-level relation extraction dataset, DocRED, which proves that it is an effective and robust document-level relation extraction framework.

Extracting biomedical relation from cross-sentence text using syntactic dependency graph attention network.

In biomedical literature, cross-sentence texts can usually express rich knowledge, and extracting the interaction relation between entities from cross-sentence texts is of great significance to biomedical research. However, compared with single sentence, cross-sentence text has a longer sequence length, so the research on cross-sentence text information extraction should focus more on learning the context dependency structural information. Nowadays, it is still a challenge to handle global dependencies and structural information of long sequences effectively, and graph-oriented modeling methods have received more and more attention recently. In this paper, we propose a new graph attention network guided by syntactic dependency relationship (SR-GAT) for extracting biomedical relation from the cross-sentence text. It allows each node to pay attention to other nodes in its neighborhood, regardless of the sequence length. The attention weight between nodes is given by a syntactic relation graph probability network (SR-GPR), which encodes the syntactic dependency between nodes and guides the graph attention mechanism to learn information about the dependency structure. The learned feature representation retains information about the node-to-node syntactic dependency, and can further discover global dependencies effectively. The experimental results demonstrate on a publicly available biomedical dataset that, our method achieves state-of-the-art performance while requiring significantly less computational resources. Specifically, in the "drug-mutation" relation extraction task, our method achieves an advanced accuracy of 93.78% for binary classification and 92.14% for multi-classification. In the "drug-gene-mutation" relation extraction task, our method achieves an advanced accuracy of 93.22% for binary classification and 92.28% for multi-classification. Across all relation extraction tasks, our method improves accuracy by an average of 0.49% compared to the existing best model. Furthermore, our method achieved an accuracy of 69.5% in text classification, surpassing most existing models, demonstrating its robustness in generalization across different domains without additional fine-tuning.

Role of soy lecithin combined with soy isoflavone on cerebral blood flow in rats of cognitive impairment and the primary screening of its optimum combination.

BACKGROUND/OBJECTIVES: Soy isoflavone (SIF) and soy lecithin (SL) have beneficial effects on many chronic diseases, including neurodegenerative diseases. Regretfully, there is little evidence to show the combined effects of these soy extractives on the impairment of cognition and abnormal cerebral blood flow (CBF). This study examined the optimal combination dose of SIF + SL to provide evidence for improving CBF and protecting cerebrovascular endothelial cells. MATERIALS/METHODS: In vivo study, SIF50 + SL40, SIF50 + SL80 and SIF50 + SL160 groups were obtained. Morris water maze, laser speckle contrast imaging (LSCI), and hematoxylin-eosin staining were used to detect learning and memory impairment, CBF, and damage to the cerebrovascular tissue in rat. The 8-hydroxy-2'-deoxyguanosine (8-OHdG) and the oxidized glutathione (GSSG) were detected. The anti-oxidative damage index of superoxide dismutase (SOD) and glutathione (GSH) in the serum of an animal model was also tested. In vitro study, an immortalized mouse brain endothelial cell line (bEND.3 cells) was used to confirm the cerebrovascular endothelial cell protection of SIF + SL. In this study, 50 µM of Gen were used, while the 25, 50, or 100 µM of SL for different incubation times were selected first. The intracellular levels of 8-OHdG, SOD, GSH, and GSSG were also detected in the cells. RESULTS: In vivo study, SIF + SL could increase the target crossing times significantly and shorten the total swimming distance of rats. The CBF in the rats of the SIF50 + SL40 group and SIF50 + SL160 group was enhanced. Pathological changes, such as attenuation of the endothelium in cerebral vessels were much less in the SIF50 + SL40 group and SIF50 + SL160 group. The 8-OHdG was reduced in the SIF50 + SL40 group. The GSSG showed a significant decrease in all SIF + SL pretreatment groups, but the GSH showed an opposite result. SOD was upregulated by SIF + SL pretreatment. Different combinations of Genistein (Gen)+SL, the secondary proof of health benefits found in vivo study, showed they have effective anti-oxidation and less side reaction on protecting cerebrovascular endothelial cell. SIF50 + SL40 in rats experiment and Gen50 + SL25 in cell test were the optimum joint doses on alleviating cognitive impairment and regulating CBF through protecting cerebrovascular tissue by its antioxidant activity. CONCLUSIONS: SIF+SL could significantly prevent cognitive defect induced by ß-Amyloid through regulating CBF. This kind of effect might be attributed to its antioxidant activity on protecting cerebral vessels.

Total inorganic nitrogen removal during the partial/complete nitrification for treating domestic wastewater: Removal pathways and main influencing factors.

Achieving nitrite accumulation was considered as the prerequisite of ANAMMOX, which hindered the application of ANAMMOX. In this study, total inorganic nitrogen (TIN) removal during the partial/complete nitrification was studied in a lab-scale sequencing batch reactor (SBR) for treating domestic wastewater. The results showed TIN was removed by denitrification, ANAMMOX and N2O emission during the partial/complete nitrification. AOB, AOA, Nitrobacter (NB), Nitrospira (NS), AnAOB and DNB were coexisted in the partial/complete nitrification. The microbial competition among these functional communities determined the type of nitrification, TIN removal and pathways. Since low DO concentrations benefits Nitrospira growth, the partial nitrification was damaged. After long-term operation, AOB gradually accommodated the low DO concentration. When Vmax,AOB (the maximum specific reaction rate of AOB) higher than Vmax,NOB (the maximum specific reaction rate of NOB), a part of nitrite was reduced by DNB and AnAOB. Therefore, TIN was removed during the complete nitrification.

Patient satisfaction with prescribed medicines in community health services in China: A cross-sectional survey 6 years after the implementation of the national essential medicines policy.

The National essential medicines policy (NEMP) is promoted by the World Health Organization for affordable medicines that can meet the basic needs of communities. Patient acceptance is essential for achieving the policy goals of the NEMP. This study aimed to assess patient satisfaction with prescribed medicines in community health services under the NEMP context in China. A stratified random sampling strategy was adopted to select 1,037 participants in 40 community health centres from four provinces in China. Patient satisfaction was rated on a five-point Likert scale (from 1 = "very dissatisfied" to 5 = "very satisfied") covering four domains: availability, affordability, effectiveness and safety. The results showed that the participants expressed a moderate degree of satisfaction, with a rating in the range of 66-82 out of a total of 100. Older people, those covered by insurance and those with a lower level of education tended to have higher ratings. While eastern (wealthy) residents were more likely to be concerned with "effectiveness," western (poor) residents were more likely to be concerned with "affordability." Awareness of the NEMP was negatively associated with patient satisfaction after control for other factors.

[N2O Production Pathways in Partial Nitrification Based on Isotope Technology].

Batch experiments were conducted under normal temperature conditions to study the generation of N2O in the partial nitrification process under different dissolved oxygen concentrations and their production pathways. When dissolved oxygen was 0.5, 1.5, and 2.5 mg·L-1, the proportion of N2O released into the total nitrogen input was 4.35%, 3.27%, and 2.63%, respectively. With increase dissolved oxygen, the proportion of N2O released to total influent nitrogen was reduced. Isotope measurements showed that when dissolved oxygen was 0.5 mg·L-1, only denitrification by ammonia-oxidizing bacteria (AOB) produced N2O. However, when dissolved oxygen increased to 1.5 mg·L-1, the activity of nitrifying bacteria increased, and 4.52% of N2O was generated through a hydroxylamine oxidation process, whereas the N2O generated by AOB denitrification accounted for 95.48%. When dissolved oxygen continuously increased to 2.5 mg·L-1, the proportion of N2O produced by hydroxylamine oxidation increased to 9.11%, and the N2O generated by AOB denitrification accounted for 90.89%. The change in dissolved oxygen concentration affects the N2O production pathway in the short-cut nitrification process, and avoiding excessive NO2--N accumulation can reduce the production of N2O.

Achieving partial denitrification through control of biofilm structure during biofilm growth in denitrifying biofilter.

Partial denitrification was one of most effective ways to provide nitrite for annamox; whereas very limited research has been done to achieve nitrite accumulation in biofilm system. In this study, partial denitrification was studied in a lab-scale denitrifying biofilter (DNBF). The results showed biofilm structure variations caused the differences between nitrate specific reduction rate (NaSRR) and nitrite specific reduction rate (NiSRR), which led to nitrite accumulation in different degree at different biofilm formation phases. Hydrodynamic conditions also significantly influenced biofilm structure, nitrate and nitrite reduction activities. At the filtration velocity of 3.86mh-1, not only biofilm structure, NaSRR and NiSRR kept relatively stable, but also 60% of nitrite accumulation and no nitrate in the effluent were achieved. Furthermore, Thauera genus bacteria, benefited for nitrite accumulation, became the dominant communities in high nitrite accumulation conditions. The partial denitrification combine with anammox in biofilter have the great potential applied in WWTPs.