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Microbotryum lychnidis-dioicae is an obligate fungal species colonizing the plant host, Silene latifolia. The fungus synthesizes and secretes effector proteins into the plant host during infection to manipulate the host for completion of the fungal lifecycle. The goal of this study was to continue functional characterization of such M. lychnidis-dioicae effectors. Here, we identified three putative effectors and their putative host-plant target proteins. MVLG_02245 is highly upregulated in M. lychnidis-dioicae during infection; yeast two-hybrid analysis suggests it targets a tubulin α-1 chain protein ortholog in the host, Silene latifolia. A potential plant protein interacting with MVLG_06175 was identified as CASP-like protein 2C1 (CASPL2C1), which facilitates the polymerization of the Casparian strip at the endodermal cells. Proteins interacting with MVLG_05122 were identified as CSN5a or 5b, involved in protein turnover. Fluorescently labelled MVLG_06175 and MVLG_05122 were expressed in the heterologous plant, Arabidopsis thaliana. MVLG_06175 formed clustered granules at the tips of trichomes on leaves and in root caps, while MVLG_05122 formed a band structure at the base of leaf trichomes. Plants expressing MVLG_05122 alone were more resistant to infection with Fusarium oxysporum. These results indicate that the fungus might affect the formation of the Casparian strip in the roots and the development of trichomes during infection as well as alter plant innate immunity. 

Abstract BackgroundThe clinical utility of machine-learning (ML) algorithms for breast cancer risk prediction and screening practices is unknown. We compared classification of lifetime breast cancer risk based on ML and the BOADICEA model. We explored the differences in risk classification and their clinical impact on screening practices. MethodsWe used three different ML algorithms and the BOADICEA model to estimate lifetime breast cancer risk in a sample of 112,587 individuals from 2481 families from the Oncogenetic Unit, Geneva University Hospitals. Performance of algorithms was evaluated using the area under the receiver operating characteristic (AU-ROC) curve. Risk reclassification was compared for 36,146 breast cancer-free women of ages 20–80. The impact on recommendations for mammography surveillance was based on the Swiss Surveillance Protocol. ResultsThe predictive accuracy of ML-based algorithms (0.843 ≤ AU-ROC ≤ 0.889) was superior to BOADICEA (AU-ROC = 0.639) and reclassified 35.3% of women in different risk categories. The largest reclassification (20.8%) was observed in women characterised as ‘near population’ risk by BOADICEA. Reclassification had the largest impact on screening practices of women younger than 50. ConclusionML-based reclassification of lifetime breast cancer risk occurred in approximately one in three women. Reclassification is important for younger women because it impacts clinical decision- making for the initiation of screening. 

Abstract The great oxidation event (GOE), ~2.4 billion years ago, caused fundamental changes to the chemistry of Earth's surface environments. However, the effect of these changes on the biosphere is unknown, due to a worldwide lack of well‐preserved fossils from this time. Here, we investigate exceptionally preserved, large spherical aggregate (SA) microfossils permineralised in chert from the c. 2.4 Ga Turee Creek Group in Western Australia. Field and petrographic observations, Raman spectroscopic mapping, and in situ carbon isotopic analyses uncover insights into the morphology, habitat, reproduction and metabolism of this unusual form, whose distinctive, SA morphology has no known counterpart in the fossil record. Comparative analysis with microfossils from before the GOE reveals the large SA microfossils represent a step‐up in cellular organisation. Morphological comparison to extant micro‐organisms indicates the SAs have more in common with coenobial algae than coccoidal bacteria, emphasising the complexity of this microfossil form. The remarkable preservation here provides a unique window into the biosphere, revealing an increase in the complexity of life coinciding with the GOE. 

Asteroid Ryugu and Ivuna-type carbonaceous meteorites may have originated from the outskirts of the Solar System.