Analysis of multiple compound–protein interactions reveals novel bioactive molecules

The authors use machine learning of compound-protein interactions to explore drug polypharmacology and to efficiently identify bioactive ligands, including novel scaffold-hopping compounds for two pharmaceutically important protein families: G-protein coupled receptors and protein kinases

NaFe0.5Co0.5O2 as high energy and power positive electrode for Na-ion batteries

O3-type NaFeO2 is a promising candidate as positive electrode materials for rechargeable Na batteries. However, its reversible range of sodium extraction is relatively narrow (x = ca. 0.4 in Na1 − xFeO2) because of the irreversible structural change, presumably associated with the iron migration into the adjacent tetrahedral sites in Na layers as we recently reported. Herein, we report that cobalt-substituted NaFeO2 demonstrates excellent electrode performance in a non-aqueous Na cell at room temperature. NaFe0.5Co0.5O2 delivers approximately 160 mAh g−1 of reversible capacity with relatively good capacity retention and excellent rate-capability in a voltage range of 2.5–4.0 V, resulting in reversible formation of Na0.3Fe0.5Co0.5O2. The partial substitution of metal element for Fe in O3-type NaFeO2-based materials is proved to be the important strategy to suppress the irreversible phase transition, and thus improving the reversibility of sodium removal/insertion as the electrode materials. Keywords: Sodium, Intercalation, Na-ion battery, NaFeO2, NaCoO

In vitro and in silico prediction of antibacterial interaction between essential oils via graph embedding approach

Abstract Essential oils contain a variety of volatile metabolites, and are expected to be utilized in wide fields such as antimicrobials, insect repellents and herbicides. However, it is difficult to foresee the effect of oil combinations because hundreds of compounds can be involved in synergistic and antagonistic interactions. In this research, it was developed and evaluated a machine learning method to classify types of (synergistic/antagonistic/no) antibacterial interaction between essential oils. Graph embedding was employed to capture structural features of the interaction network from literature data, and was found to improve in silico predicting performances to classify synergistic interactions. Furthermore, in vitro antibacterial assay against a standard strain of Staphylococcus aureus revealed that four essential oil pairs (Origanum compactum—Trachyspermum ammi, Cymbopogon citratus—Thujopsis dolabrata, Cinnamomum verum—Cymbopogon citratus and Trachyspermum ammi—Zingiber officinale) exhibited synergistic interaction as predicted. These results indicate that graph embedding approach can efficiently find synergistic interactions between antibacterial essential oils

A case of airway aluminosis with likely secondary pleuroparenchymal fibroelastosis

Abstract Background Excessive inhalation of aluminium powder occasionally results in upper lobe predominant lung fibrosis, which is similar to idiopathic pleuroparenchymal fibroelastosis (IPPFE) and has been suggested to be secondary PPFE. Case presentation A 67-year-old man who had worked in an aluminum-processing factory for 50 years visited our hospital complaining of exertional dyspnea. Chest computed tomography (CT) showed bilateral dense sub-pleural consolidation in the upper and middle lung fields, which was consistent with IPPFE; however, the possibility of secondary PPFE associated with aluminosis was not ruled out. Considering the patient’s critical condition, trans-bronchial lung biopsy (TBLB) rather than surgical lung biopsy was performed, with elemental analysis of the biopsied specimen. Unfortunately, the specimen obtained by TBLB did not contain alveolar tissue; therefore, pathological diagnosis of PPFE was not possible. However, radiographic findings were highly suggestive of PPFE. On elemental analysis, excessive amounts of aluminum were detected in the bronchiolar walls, establishing a diagnosis of airway aluminosis with likely secondary PPFE resulting from aluminium exposure. Conclusions TBLB with elemental analysis might be useful in differentiating idiopathic PPFE from secondary causes in dust inhalation related disease, such as aluminosis. This case indicated that inhalation of aluminium might cause secondary PPFE, with attention needing to be paid to avoid further exposure