Dynamical Masses for Low-Mass Pre-Main Sequence Stars: A Preliminary Physical Orbit for HD 98800 B

We report on Keck Interferometer observations of the double-lined binary (B) component of the quadruple pre-main sequence (PMS) system HD 98800. With these interferometric observations combined with astrometric measurements made by the Hubble Space Telescope Fine Guidance Sensors (FGS), and published radial velocity observations we have estimated preliminary visual and physical orbits of the HD 98800 B subsystem. Our orbit model calls for an inclination of 66.8 $\pm$ 3.2 deg, and allows us to infer the masses and luminosities of the individual components. In particular we find component masses of 0.699 $\pm$ 0.064 and 0.582 $\pm$ 0.051 M_{\sun} for the Ba (primary) and Bb (secondary) components respectively. Modeling of the component SEDs finds temperatures and luminosities in agreement with previous studies, and coupled with the component mass estimates allows for comparison with PMS models in the low-mass regime with few empirical constraints. Solar abundance models seem to under-predict the inferred component temperatures and luminosities, while assuming slightly sub-solar abundances bring the models and observations into better agreement. The present preliminary orbit does not yet place significant constraints on existing pre-main sequence stellar models, but prospects for additional observations improving the orbit model and component parameters are very good.Comment: 20 pages, 6 figures, ApJ in press; tables 2 and 3 to be included in ApJ versio

Dynamical Masses for Pre-Main Sequence Stars: A Preliminary Physical Orbit for V773 Tau A

We report on interferometric and radial-velocity observations of the double-lined 51-d period binary (A) component of the quadruple pre-main sequence (PMS) system V773 Tau. With these observations we have estimated preliminary visual and physical orbits of the V773 Tau A subsystem. Among other parameters, our orbit model includes an inclination of 66.0 $\pm$ 2.4 deg, and allows us to infer the component dynamical masses and system distance. In particular we find component masses of 1.54 $\pm$ 0.14 and 1.332 $\pm$ 0.097 M_{\sun} for the Aa (primary) and Ab (secondary) components respectively. Our modeling of the subsystem component spectral energy distributions finds temperatures and luminosities consistent with previous studies, and coupled with the component mass estimates allows for comparison with PMS stellar models in the intermediate-mass range. We compare V773 Tau A component properties with several popular solar-composition models for intermediate-mass PMS stars. All models predict masses consistent to within 2-sigma of the dynamically determined values, though some models predict values that are more consistent than others.Comment: ApJ in press; 25 pages, 6 figures; data tables available in journal versio

VLA FRAMEx. I. Wideband Radio Properties of the AGN in NGC 4388

We present the first results from Karl G. Jansky Very Large Array (VLA) observations as a part of the Fundamental Reference Active Galactic Nucleus (AGN) Monitoring Experiment (FRAMEx), a program to understand the relationship between AGN accretion physics and wavelength-dependent position as a function of time. With this VLA survey, we investigate the radio properties from a volume-complete sample of 25 hard X-ray-selected AGNs using the VLA in its wideband mode. We observed the targets in the A-array configuration at $4-12$ GHz with all polarization products. In this work, we introduce our calibration and imaging methods for this survey, and we present our results and analysis for the radio quiet AGN NGC 4388. We calibrated and imaged these data using the multi-term, multi-frequency synthesis imaging algorithm to determine its spatial, spectral and polarization structure across a continuous $4-12$ GHz band. In the AGN, we measure a broken power law spectrum with $\alpha=-0.06$ below a break frequency of 7.3 GHz and $\alpha=-0.34$ above. We detect polarization at sub-arcsecond resolution across both the AGN and a secondary radio knot. We compare our results to ancillary data and find that the VLA radio continuum is likely due to AGN winds interacting with the local interstellar medium that gets resolved away at sub-parsec spatial scales as probed by the Very Long Baseline Array. A well-known ionization cone to the southwest of the AGN appears likely to be projected material onto the underside of the disk of the host galaxy.Comment: 22 pages, 9 figures, Accepted in Ap

Decarboxylative and dehydrative coupling of dienoic acids and pentadienyl alcohols to form 1,3,6,8-tetraenes

Dienoic acids and pentadienyl alcohols are coupled in a decarboxylative and dehydrative manner at ambient temperature using Pd(0) catalysis to generate 1,3,6,8-tetraenes. Contrary to related decarboxylative coupling reactions, an anion-stabilizing group is not required adjacent to the carboxyl group. Of mechanistic importance, it appears that both the diene of the acid and the diene of the alcohol are required for this reaction. To further understand this reaction, substitutions at every unique position of both cou- pling partners was examined and two potential mechanisms are presented

Patient-centric trials for therapeutic development in precision oncology

An enhanced understanding of the molecular pathology of disease gained from genomic studies is facilitating the development of treatments that target discrete molecular subclasses of tumours. Considerable associated challenges include how to advance and implement targeted drug-development strategies. Precision medicine centres on delivering the most appropriate therapy to a patient on the basis of clinical and molecular features of their disease. The development of therapeutic agents that target molecular mechanisms is driving innovation in clinical-trial strategies. Although progress has been made, modifications to existing core paradigms in oncology drug development will be required to realize fully the promise of precision medicine

Enhancing easy-plane anisotropy in bespoke Ni(II) quantum magnets

We examine the crystal structures and magnetic properties of several S = 1 Ni(II) coordination compounds, molecules and polymers, that include the bridging ligands HF2-, AF62- (A = Ti, Zr) and pyrazine or non-bridging ligands F-, SiF62-, glycine, H2O, 1-vinylimidazole, 4-methylpyrazole and 3-hydroxypyridine. Pseudo-octahedral NiN4F2, NiN4O2 or NiN4OF cores consist of equatorial Ni-N bonds that are equal to or slightly longer than the axial Ni-Lax bonds. By design, the zero-field splitting (D) is large in these systems and, in the presence of substantial exchange interactions (J), can be difficult to discriminate from magnetometry measurements on powder samples. Thus, we relied on pulsed-field magnetization in those cases and employed electron-spin resonance (ESR) to confirm D when J 0) and range from ≈ 8-25 K. This work reveals a linear correlation between the ratio d(Ni-Lax)/d(Ni-Neq) and D although the ligand spectrochemical properties may also be important. We assert that this relationship allows us to predict the type of magnetocrystalline anisotropy in tailored Ni(II) quantum magnets

Multi-modality machine learning predicting Parkinson's disease

Personalized medicine promises individualized disease prediction and treatment. The convergence of machine learning (ML) and available multimodal data is key moving forward. We build upon previous work to deliver multimodal predictions of Parkinson's disease (PD) risk and systematically develop a model using GenoML, an automated ML package, to make improved multi-omic predictions of PD, validated in an external cohort. We investigated top features, constructed hypothesis-free disease-relevant networks, and investigated drug-gene interactions. We performed automated ML on multimodal data from the Parkinson's progression marker initiative (PPMI). After selecting the best performing algorithm, all PPMI data was used to tune the selected model. The model was validated in the Parkinson's Disease Biomarker Program (PDBP) dataset. Our initial model showed an area under the curve (AUC) of 89.72% for the diagnosis of PD. The tuned model was then tested for validation on external data (PDBP, AUC 85.03%). Optimizing thresholds for classification increased the diagnosis prediction accuracy and other metrics. Finally, networks were built to identify gene communities specific to PD. Combining data modalities outperforms the single biomarker paradigm. UPSIT and PRS contributed most to the predictive power of the model, but the accuracy of these are supplemented by many smaller effect transcripts and risk SNPs. Our model is best suited to identifying large groups of individuals to monitor within a health registry or biobank to prioritize for further testing. This approach allows complex predictive models to be reproducible and accessible to the community, with the package, code, and results publicly available

Bolocam Survey for 1.1 mm Dust Continuum Emission in the c2d Legacy Clouds

ABSTRACT We have completed a