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IntroductionModern understanding of the concept of genetic diversity must include the study of both nuclear and organellar DNA, which differ greatly in terms of their structure, organization, gene content and distribution. This study comprises an analysis of the genetic diversity of the smut fungusSporisorium reilianumf. sp.zeaefrom a mitochondrial perspective. MethodsWhole-genome sequencing data was generated from biological samples ofS. reilianumcollected from different geographical regions. Multiple sequence alignment and gene synteny analysis were performed to further characterize genetic diversity in the context of mitogenomic polymorphisms. ResultsMitochondria of strains collected in China contained unique sequences. The largest unique sequence stretch encompassed a portion ofcox1, a mitochondrial gene encoding one of the subunits that make up complex IV of the mitochondrial electron transport chain. This unique sequence had high percent identity to the mitogenome of the related speciesSporisorium scitamineumandUstilago bromivora. DiscussionThe results of this study hint at potential horizontal gene transfer or mitochondrial genome recombination events during the evolutionary history of basidiomycetes. Additionally, the distinct polymorphic region detected in the Chinese mitogenome provides the ideal foundation to develop a diagnostic method to discern between mitotypes and enhance knowledge on the genetic diversity of this organism. 

Abstract The purpose of this study is to identify additional clinical features for sepsis detection through the use of a novel mechanism for interpreting black-box machine learning models trained and to provide a suitable evaluation for the mechanism. We use the publicly available dataset from the 2019 PhysioNet Challenge. It has around 40,000 Intensive Care Unit (ICU) patients with 40 physiological variables. Using Long Short-Term Memory (LSTM) as the representative black-box machine learning model, we adapted the Multi-set Classifier to globally interpret the black-box model for concepts it learned about sepsis. To identify relevant features, the result is compared against: (i) features used by a computational sepsis expert, (ii) clinical features from clinical collaborators, (iii) academic features from literature, and (iv) significant features from statistical hypothesis testing. Random Forest was found to be the computational sepsis expert because it had high accuracies for solving both the detection and early detection, and a high degree of overlap with clinical and literature features. Using the proposed interpretation mechanism and the dataset, we identified 17 features that the LSTM used for sepsis classification, 11 of which overlaps with the top 20 features from the Random Forest model, 10 with academic features and 5 with clinical features. Clinical opinion suggests, 3 LSTM features have strong correlation with some clinical features that were not identified by the mechanism. We also found that age, chloride ion concentration, pH and oxygen saturation should be investigated further for connection with developing sepsis. Interpretation mechanisms can bolster the incorporation of state-of-the-art machine learning models into clinical decision support systems, and might help clinicians to address the issue of early sepsis detection. The promising results from this study warrants further investigation into creation of new and improvement of existing interpretation mechanisms for black-box models, and into clinical features that are currently not used in clinical assessment of sepsis. 

Abstract Organismal physiology is widely regulated by the molecular circadian clock, a feedback loop composed of protein complexes whose members are enriched in intrinsically disordered regions. These regions can mediate protein-protein interactions via SLiMs, but the contribution of these disordered regions to clock protein interactions had not been elucidated. To determine the functionality of these disordered regions, we applied a synthetic peptide microarray approach to the disordered clock protein FRQ inNeurospora crassa. We identified residues required for FRQ’s interaction with its partner protein FRH, the mutation of which demonstrated FRH is necessary for persistent clock oscillations but not repression of transcriptional activity. Additionally, the microarray demonstrated an enrichment of FRH binding to FRQ peptides with a net positive charge. We found that positively charged residues occurred in significant “blocks” within the amino acid sequence of FRQ and that ablation of one of these blocks affected both core clock timing and physiological clock output. Finally, we found positive charge clusters were a commonly shared molecular feature in repressive circadian clock proteins. Overall, our study suggests a mechanistic purpose for positive charge blocks and yielded insights into repressive arm protein roles in clock function. 

ABSTRACT We present updated orbital elements for the Wolf–Rayet (WR) binary WR 140 (HD 193793; WC7pd  + O5.5fc). The new orbital elements were derived using previously published measurements along with 160 new radial velocity measurements across the 2016 periastron passage of WR 140. Additionally, four new measurements of the orbital astrometry were collected with the CHARA Array. With these measurements, we derive stellar masses of $$M_{\rm WR} = 10.31\pm 0.45 \, \mathrm{M}_\odot$$ and $$M_{\rm O} = 29.27\pm 1.14 \, \mathrm{M}_{\odot }$$. We also include a discussion of the evolutionary history of this system from the Binary Population and Spectral Synthesis model grid to show that this WR star likely formed primarily through mass-loss in the stellar winds, with only a moderate amount of mass lost or transferred through binary interactions. 

ABSTRACT The bright and understudied classical Be star HD 6226 has exhibited multiple outbursts in the last several years during which the star grew a viscous decretion disc. We analyse 659 optical spectra of the system collected from 2017 to 2020, along with a ultraviolet spectrum from the Hubble Space Telescope and high cadence photometry from both Transiting Exoplanet Survey Satellite (TESS) and the Kilodegree Extremely Little Telescope (KELT) survey. We find that the star has a spectral type of B2.5IIIe, with a rotation rate of 74 per cent of critical. The star is nearly pole-on with an inclination of 13$${_{.}^{\circ}}$$4. We confirm the spectroscopic pulsational properties previously reported, and report on three photometric oscillations from KELT photometry. The outbursting behaviour is studied with equivalent width measurements of H α and H β, and the variations in both of these can be quantitatively explained with two frequencies through a Fourier analysis. One of the frequencies for the emission outbursts is equal to the difference between two photometric oscillations, linking these pulsation modes to the mass ejection mechanism for some outbursts. During the TESS observation time period of 2019 October 7 to 2019 November 2, the star was building a disc. With a large data set of H α and H β spectroscopy, we are able to determine the time-scales of dissipation in both of these lines, similar to past work on Be stars that has been done with optical photometry. HD 6226 is an ideal target with which to study the Be disc-evolution given its apparent periodic nature, allowing for targeted observations with other facilities in the future.