Atomic-scale control of magnetic anisotropy via novel spin-orbit coupling effect in La2/3Sr1/3MnO3/SrIrO3 superlattices

Magnetic anisotropy (MA) is one of the most important material properties for modern spintronic devices. Conventional manipulation of the intrinsic MA, i.e. magnetocrystalline anisotropy (MCA), typically depends upon crystal symmetry. Extrinsic control over the MA is usually achieved by introducing shape anisotropy or exchange bias from another magnetically ordered material. Here we demonstrate a pathway to manipulate MA of 3d transition metal oxides (TMOs) by digitally inserting non-magnetic 5d TMOs with pronounced spin-orbit coupling (SOC). High quality superlattices comprised of ferromagnetic La2/3Sr1/3MnO3 (LSMO) and paramagnetic SrIrO3 (SIO) are synthesized with the precise control of thickness at atomic scale. Magnetic easy axis reorientation is observed by controlling the dimensionality of SIO, mediated through the emergence of a novel spin-orbit state within the nominally paramagnetic SIO.Comment: Proceedings of the National Academy of Sciences, May 201

Enhanced bioremediation of aged polycyclic aromatic hydrocarbons in soil using immobilized microbial consortia combined with strengthening remediation strategies

Microbial biodegradation is considered as one of the most effective strategies for the remediation of soil contaminated with polycyclic aromatic hydrocarbons (PAHs). To improve the degradation efficiency of PAHs, PAH-degrading consortia combined with strengthening remediation strategies was used in this study. The PAH biodegrading performance of seven bacterial consortia constructed by different ratios of Mycobacterium gilvum MI, Mycobacterium sp. ZL7 and Rhodococcus rhodochrous Q3 was evaluated in an aqueous system containing phenanthrene, pyrene, benzo[a]pyrene and benzo[b]fluoranthene. Bacterial consortium H6 (Q3:ZL7:MI = 1:2:2) performed a high degrading efficiency of 59% in 8 days. The H6 was subsequently screened to explore its potential ability and performance to degrade aged PAHs in soils from a coking plant and the effects of strengthening strategies on the aged PAH degradation, including the addition of glucose or sodium dodecyl benzene sulfonate (SDBS) individually or as a mixture along immobilization of the inoculant on biochar. The highest degradation efficiencies, which were 15% and 60% for low-molecular-weight (LMW) PAHs and high-molecular-weight (HMW) PAHs, respectively, were observed in the treatment using immobilized microbial consortium H6 combined with the addition of glucose and SDBS after 24 days incubation. This study provides new insights and guidance for future remediation of aged PAH contaminated soils

Gremlin1 Delivered by Mesenchymal Stromal Cells Promoted Epithelial-Mesenchymal Transition in Human Esophageal Squamous Cell Carcinoma

Backgroud/Aims: Mesenchymal stromal cells (MSCs) are a major component of the tumor microenvironment (TME). Several studies focusing on tumor-derived MSCs have demonstrated that they exhibit a strong ability to promote the tumor epithelial-mesenchymal transition (EMT). However, the factors mediating these effects are poorly understood. Methods: Quantitative reverse transcription-polymerase chain reaction (qRT-PCR) and immunohistochemistry assays were used to detect the expression of Gremlin1 (GREM1) in human esophageal squamous cell carcinoma (ESCC) tissues. ShRNA silencing, flow cytometry, cell counting kit (CCK8) assay, invasion assay, western blot were used to detect the effect of GREM1 in ECa109, TE-1 cell lines and xenograft tumor models. Results: In the current study, we found that the GREM1 was overexpressed in human ESCC tissues. The conditioned medium from mesenchymal stromal cells (MSCs-CM) enhanced the malignancy of xenograft esophageal tumors in vivo, as well as the cell proliferation, viability and invasion of the esophageal carcinoma cell lines ECa109 and TE-1 in vitro. Furthermore, the shRNA silencing of GREM1 in MSCs (shGREM1-MSCs) reversed the increased malignancy of the esophageal tumor in vivo, while the conditioned medium from shGREM1-MSCs (shGREM1-MSCs-CM) affected the cell cycle and cell invasion in vitro. These processes were accompanied by the EMT in the ECa109 and TE-1 cell lines with an alteration in the expression levels of mesenchymal and epithelial markers. Furthermore, the TGF-β/BMP (transforming growth factor-beta/bone morphogenetic protein) signaling pathway participated in the shGREM1-MSCs-CM-induced anti-tumor effect on enhanced esophageal malignancy induced by MSCs-CM treatment. Conclusions: Taken together, our study suggested that GREM1 delivered by MSCs promoted EMT in ESCC in vitro and in vivo, which is partly through TGF-β/BMP signaling pathway. The results provide experimental evidence to a potential therapeutic target in the treatment of esophageal cancer

The CAFA challenge reports improved protein function prediction and new functional annotations for hundreds of genes through experimental screens

Background The Critical Assessment of Functional Annotation (CAFA) is an ongoing, global, community-driven effort to evaluate and improve the computational annotation of protein function. Results Here, we report on the results of the third CAFA challenge, CAFA3, that featured an expanded analysis over the previous CAFA rounds, both in terms of volume of data analyzed and the types of analysis performed. In a novel and major new development, computational predictions and assessment goals drove some of the experimental assays, resulting in new functional annotations for more than 1000 genes. Specifically, we performed experimental whole-genome mutation screening in Candida albicans and Pseudomonas aureginosa genomes, which provided us with genome-wide experimental data for genes associated with biofilm formation and motility. We further performed targeted assays on selected genes in Drosophila melanogaster, which we suspected of being involved in long-term memory. Conclusion We conclude that while predictions of the molecular function and biological process annotations have slightly improved over time, those of the cellular component have not. Term-centric prediction of experimental annotations remains equally challenging; although the performance of the top methods is significantly better than the expectations set by baseline methods in C. albicans and D. melanogaster, it leaves considerable room and need for improvement. Finally, we report that the CAFA community now involves a broad range of participants with expertise in bioinformatics, biological experimentation, biocuration, and bio-ontologies, working together to improve functional annotation, computational function prediction, and our ability to manage big data in the era of large experimental screens.Peer reviewe

An expanded evaluation of protein function prediction methods shows an improvement in accuracy

Background: A major bottleneck in our understanding of the molecular underpinnings of life is the assignment of function to proteins. While molecular experiments provide the most reliable annotation of proteins, their relatively low throughput and restricted purview have led to an increasing role for computational function prediction. However, assessing methods for protein function prediction and tracking progress in the field remain challenging. Results: We conducted the second critical assessment of functional annotation (CAFA), a timed challenge to assess computational methods that automatically assign protein function. We evaluated 126 methods from 56 research groups for their ability to predict biological functions using Gene Ontology and gene-disease associations using Human Phenotype Ontology on a set of 3681 proteins from 18 species. CAFA2 featured expanded analysis compared with CAFA1, with regards to data set size, variety, and assessment metrics. To review progress in the field, the analysis compared the best methods from CAFA1 to those of CAFA2. Conclusions: The top-performing methods in CAFA2 outperformed those from CAFA1. This increased accuracy can be attributed to a combination of the growing number of experimental annotations and improved methods for function prediction. The assessment also revealed that the definition of top-performing algorithms is ontology specific, that different performance metrics can be used to probe the nature of accurate predictions, and the relative diversity of predictions in the biological process and human phenotype ontologies. While there was methodological improvement between CAFA1 and CAFA2, the interpretation of results and usefulness of individual methods remain context-dependent. Keywords: Protein function prediction, Disease gene prioritizationpublishedVersio

An Expanded Evaluation of Protein Function Prediction Methods Shows an Improvement In Accuracy

Background: A major bottleneck in our understanding of the molecular underpinnings of life is the assignment of function to proteins. While molecular experiments provide the most reliable annotation of proteins, their relatively low throughput and restricted purview have led to an increasing role for computational function prediction. However, assessing methods for protein function prediction and tracking progress in the field remain challenging. Results: We conducted the second critical assessment of functional annotation (CAFA), a timed challenge to assess computational methods that automatically assign protein function. We evaluated 126 methods from 56 research groups for their ability to predict biological functions using Gene Ontology and gene-disease associations using Human Phenotype Ontology on a set of 3681 proteins from 18 species. CAFA2 featured expanded analysis compared with CAFA1, with regards to data set size, variety, and assessment metrics. To review progress in the field, the analysis compared the best methods from CAFA1 to those of CAFA2. Conclusions: The top-performing methods in CAFA2 outperformed those from CAFA1. This increased accuracy can be attributed to a combination of the growing number of experimental annotations and improved methods for function prediction. The assessment also revealed that the definition of top-performing algorithms is ontology specific, that different performance metrics can be used to probe the nature of accurate predictions, and the relative diversity of predictions in the biological process and human phenotype ontologies. While there was methodological improvement between CAFA1 and CAFA2, the interpretation of results and usefulness of individual methods remain context-dependent

The CAFA challenge reports improved protein function prediction and new functional annotations for hundreds of genes through experimental screens

BackgroundThe Critical Assessment of Functional Annotation (CAFA) is an ongoing, global, community-driven effort to evaluate and improve the computational annotation of protein function.ResultsHere, we report on the results of the third CAFA challenge, CAFA3, that featured an expanded analysis over the previous CAFA rounds, both in terms of volume of data analyzed and the types of analysis performed. In a novel and major new development, computational predictions and assessment goals drove some of the experimental assays, resulting in new functional annotations for more than 1000 genes. Specifically, we performed experimental whole-genome mutation screening in Candida albicans and Pseudomonas aureginosa genomes, which provided us with genome-wide experimental data for genes associated with biofilm formation and motility. We further performed targeted assays on selected genes in Drosophila melanogaster, which we suspected of being involved in long-term memory.ConclusionWe conclude that while predictions of the molecular function and biological process annotations have slightly improved over time, those of the cellular component have not. Term-centric prediction of experimental annotations remains equally challenging; although the performance of the top methods is significantly better than the expectations set by baseline methods in C. albicans and D. melanogaster, it leaves considerable room and need for improvement. Finally, we report that the CAFA community now involves a broad range of participants with expertise in bioinformatics, biological experimentation, biocuration, and bio-ontologies, working together to improve functional annotation, computational function prediction, and our ability to manage big data in the era of large experimental screens.</p