Community knowledge graph abstraction for enhanced link prediction: A study on PubMed knowledge graph.

OBJECTIVE: As new knowledge is produced at a rapid pace in the biomedical field, existing biomedical Knowledge Graphs (KGs) cannot be manually updated in a timely manner. Previous work in Natural Language Processing (NLP) has leveraged link prediction to infer the missing knowledge in general-purpose KGs. Inspired by this, we propose to apply link prediction to existing biomedical KGs to infer missing knowledge. Although Knowledge Graph Embedding (KGE) methods are effective in link prediction tasks, they are less capable of capturing relations between communities of entities with specific attributes (Fanourakis et al., 2023). METHODS: To address this challenge, we proposed an entity distance-based method for abstracting a Community Knowledge Graph (CKG) from a simplified version of the pre-existing PubMed Knowledge Graph (PKG) (Xu et al., 2020). For link prediction on the abstracted CKG, we proposed an extension approach for the existing KGE models by linking the information in the PKG to the abstracted CKG. The applicability of this extension was proved by employing six well-known KGE models: TransE, TransH, DistMult, ComplEx, SimplE, and RotatE. Evaluation metrics including Mean Rank (MR), Mean Reciprocal Rank (MRR), and Hits@k were used to assess the link prediction performance. In addition, we presented a backtracking process that traces the results of CKG link prediction back to the PKG scale for further comparison. RESULTS: Six different CKGs were abstracted from the PKG by using embeddings of the six KGE methods. The results of link prediction in these abstracted CKGs indicate that our proposed extension can improve the existing KGE methods, achieving a top-10 accuracy of 0.69 compared to 0.5 for TransE, 0.7 compared to 0.54 for TransH, 0.67 compared to 0.6 for DistMult, 0.73 compared to 0.57 for ComplEx, 0.73 compared to 0.63 for SimplE, and 0.85 compared to 0.76 for RotatE on their CKGs, respectively. These improved performances also highlight the wide applicability of the extension approach. CONCLUSION: This study proposed novel insights into abstracting CKGs from the PKG. The extension approach indicated enhanced performance of the existing KGE methods and has applicability. As an interesting future extension, we plan to conduct link prediction for entities that are newly introduced to the PKG.

Improvement of intervention information detection for automated clinical literature screening during systematic review.

Systematic literature review (SLR) is a crucial method for clinicians and policymakers to make their decisions in a flood of new clinical studies. Because manual literature screening in SLR is a highly laborious task, its automation by natural language processing (NLP) has been welcomed. Although intervention is a key information for literature screening, NLP models for its detection in previous works have not shown adequate performance. In this work, we first design an algorithm for automated construction of high-quality intervention labels by utilizing information retrieved from a clinical trial database. We then design another algorithm for improving model's recall and F1 score by imposing adaptive weights on training instances in the loss function. The intervention detection model trained on the weighted datasets is tested with the Evidence-Based Medicine NLP (EBM-NLP) corpus, and shows 9.7% and 4.0% improvements respectively in recall and F1 score compared to the previous state-of-the-art model on the corpus. The proposed algorithms can boost automation of literature screening during SLR in the clinical domain.

Transforming growth factor-ß2 is sequestered in preterm human milk by chondroitin sulfate proteoglycans.

Human milk contains biologically important amounts of transforming growth factor-ß2 isoform (TGF-ß2), which is presumed to protect against inflammatory gut mucosal injury in the neonate. In preclinical models, enterally administered TGF-ß2 can protect against experimental necrotizing enterocolitis, an inflammatory bowel necrosis of premature infants. In this study, we investigated whether TGF-ß bioactivity in human preterm milk could be enhanced for therapeutic purposes by adding recombinant TGF-ß2 (rTGF-ß2) to milk prior to feeding. Milk-borne TGF-ß bioactivity was measured by established luciferase reporter assays. Molecular interactions of TGF-ß2 were investigated by nondenaturing gel electrophoresis and immunoblots, computational molecular modeling, and affinity capillary electrophoresis. Addition of rTGF-ß2 (20-40 nM) to human preterm milk samples failed to increase TGF-ß bioactivity in milk. Milk-borne TGF-ß2 was bound to chondroitin sulfate (CS) containing proteoglycan(s) such as biglycan, which are expressed in high concentrations in milk. Chondroitinase treatment of milk increased the bioactivity of both endogenous and rTGF-ß2, and consequently, enhanced the ability of preterm milk to suppress LPS-induced NF-κB activation in macrophages. These findings provide a mechanism for the normally low bioavailability of milk-borne TGF-ß2 and identify chondroitinase digestion of milk as a potential therapeutic strategy to enhance the anti-inflammatory effects of preterm milk.

Investigation of the heparin-thrombin interaction by dynamic force spectroscopy.

BACKGROUND: The interaction between heparin and thrombin is a vital step in the blood (anti)coagulation process. Unraveling the molecular basis of the interactions is therefore extremely important in understanding the mechanisms of this complex biological process. METHODS: In this study, we use a combination of an efficient thiolation chemistry of heparin, a self-assembled monolayer-based single molecule platform, and a dynamic force spectroscopy to provide new insights into the heparin-thrombin interaction from an energy viewpoint at the molecular scale. RESULTS: Well-separated single molecules of heparin covalently attached to mixed self-assembled monolayers are demonstrated, whereby interaction forces with thrombin can be measured via atomic force microscopy-based spectroscopy. Further these interactions are studied at different loading rates and salt concentrations to directly obtain kinetic parameters. CONCLUSIONS: An increase in the loading rate shows a higher interaction force between the heparin and thrombin, which can be directly linked to the kinetic dissociation rate constant (koff). The stability of the heparin/thrombin complex decreased with increasing NaCl concentration such that the off-rate was found to be driven primarily by non-ionic forces. GENERAL SIGNIFICANCE: These results contribute to understanding the role of specific and nonspecific forces that drive heparin-thrombin interactions under applied force or flow conditions.

An update on recent patents on thrombin inhibitors (2010 - 2013).

INTRODUCTION: Thromboembolic incidences have increased nearly 33% in the past decade and directly affect nearly 0.5% of the population. Heparin, warfarin and current direct thrombin inhibitors (DTIs), the primary anticoagulants of choice, suffer from several drawbacks. Thus, the search for an antithrombotic devoid of adverse effect continues in earnest. AREAS COVERED: Literature search covering PubMed, SciFinder(™) Scholar, Web of Knowledge, Espacenet, PatentScope and Google Patent Search was used to uncover > 35 patents describing new chemical entities and advances in DTI technologies. Our search uncovered considerable emphasis on the development of larger more complex molecules such as peptide-based inhibitors, prodrug derivatives, bivalent tryptophan zippers, triple action inhibitors and allosteric inhibitors. Advances in formulation technologies for clinically relevant DTIs have also been made. EXPERT OPINION: Thrombin is a multifaceted, dynamic enzyme with both coagulant and anticoagulant functions. Newer DTIs are attempting to fine tune thrombin's activity by targeting allosteric sites or by site-specific targeting of clotting. The complexity of thrombin's functions is driving the design of complex anticoagulants. Advancements in formulations and production processes have attempted to make traditional DTIs more cost effective to produce. The literature reveals a trend to develop a thrombin 'modulator' rather than an 'inhibitor.'

[The research of basic medical education with clinical practice and culturing of discovering and creative ability for students].

In order to explore the educational model of combined research aidding basic medical education and clinical practice, the educational form of combined research, teaching and clinical practice was adopted and brought into the education of medical genetics for medical students. The consequence of five-year educational practice has revealed that the educational effects and quality have been obviously increased, and the deeply activated studying initiative, self-studying ability, ability of cooperation, discovering and creative ability have been achieved in culturing practical general medical students with in-depth basic knowledge, great ability and high quality.