Publisher Correction: Capturing variation impact on molecular interactions in the IMEx Consortium mutations data set

Maximized Schottky Effect: The Ultrafine V2 O3 /Ni Heterojunctions Repeatedly Arranging on Monolayer Nanosheets for Efficient and Stable Water-to-Hydrogen Conversion

The Mott-Schottky heterojunction formed at the interface of ultrafine metallic Ni and semiconducting V₂ O₃ nanoparticles is constructed, and the heterojunctions are "knitted" into the tulle-like monolayer nanosheets on nickel foam (NF). The greatly reduced particle sizes of both Ni and V₂ O₃ on the Mott-Schottky heterojunction highly enhance the number of Schottky heterojunctions per unit area of the materials. Moreover, arranging the heterojunctions into the monolayer nanosheets makes the heterojunctions repeat and expose to the electrolyte sufficiently. The Schottky heterojunctions are like countless self-powered charge transfer workstations embedded in the tulle-like monolayer nanosheets, promoting maximum of the materials to participate into the electron transfer and become catalytic active sites. In addition, the tulle-like monolayer nanosheet structure can assist in pumping liquid phase electrolyte to the surface of catalysts, owing to the capillary force. The V₂ O₃ /Ni/NF Mott-Schottky catalyst exhibits excellent hydrogen evolution reaction (HER) performance with a low η₁₀ of 54 mV and needs -107 mV to get the current density of -100 mA cm^-2 . Furthermore, V₂ O₃ /Ni/NF Schottky electrocatalyst exhibits excellent urea oxidation reaction activity: 1.40, 1.51, and 1.61 V versus reversible hydrogen electrode (RHE) voltage are required to reach a current density of 100, 500, and 1000 mA cm^-2 , respectively.

The first 10 years of the international coordination network for standards in systems and synthetic biology (COMBINE)

This paper presents a report on outcomes of the 10th Computational Modeling in Biology Network (COMBINE) meeting that was held in Heidelberg, Germany, in July of 2019. The annual event brings together researchers, biocurators and software engineers to present recent results and discuss future work in the area of standards for systems and synthetic biology. The COMBINE initiative coordinates the development of various community standards and formats for computational models in the life sciences. Over the past 10 years, COMBINE has brought together standard communities that have further developed and harmonized their standards for better interoperability of models and data. COMBINE 2019 was co-located with a stakeholder workshop of the European EU-STANDS4PM initiative that aims at harmonized data and model standardization for in silico models in the field of personalized medicine, as well as with the FAIRDOM PALs meeting to discuss findable, accessible, interoperable and reusable (FAIR) data sharing. This report briefly describes the work discussed in invited and contributed talks as well as during breakout sessions. It also highlights recent advancements in data, model, and annotation standardization efforts. Finally, this report concludes with some challenges and opportunities that this community will face during the next 10 years.

TP53 mutations in high grade serous ovarian cancer and impact on clinical outcomes: a comparison of next generation sequencing and bioinformatics analyses

Objective

Mutations in TP53 are found in the majority of high grade serous ovarian cancers, leading to gain of function or loss of function of its protein product, p53, involved in oncogenesis. There have been conflicting reports as to the impact of the type of these on prognosis. We aim to further elucidate this relationship in our cohort of patients.

Methods

229 patients with high grade serous ovarian cancer underwent tumor profiling through an institutional molecular screening program with targeted next generation sequencing. TP53 mutations were classified using methods previously described in the literature. Immunohistochemistry on formalin-fixed paraffin embedded tissue was used to assess for TP53 mutation. Using divisive hierarchal clustering, we generated patient clusters with similar clinicopathologic characteristics to investigate differences in outcomes.

Results

Six different classification schemes of TP53 mutations were studied. These did not show an association with first platinum-free interval or overall survival. Next generation sequencing reliably predicted mutation in 80% of cases, similar to the proportion detected by immunohistochemistry. Divisive hierarchical clustering generated four main clusters, with cluster 3 having a significantly worse prognosis (p<0.0001; log-rank test). This cluster had a higher concentration of gain of function mutations and these patients were less likely to have undergone optimal debulking surgery.

Conclusions

Different classifications of TP53 mutations did not show an impact on outcomes in this study. Immunohistochemistry was a good predictor for TP53 mutation. Cluster analysis showed that a subgroup of patients with gain of function mutations (cluster 3) had a worse prognosis.