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Polycyclic aromatic hydrocarbons (PAHs) are among the most ubiquitous compounds in the universe, accounting for up to ~25% of all interstellar carbon. Since most unsubstituted PAHs do not possess permanent dipole moments, they are invisible to radio astronomy. Constraining their abundances relies on the detection of polar chemical proxies, such as aromatic nitriles. We report the detection of 2- and 4-cyanopyrene, isomers of the recently detected 1-cyanopyrene. We find that these isomers are present in an abundance ratio of ~2:1:2, which mirrors the number of equivalent sites available for CN addition. We conclude that there is evidence that the cyanopyrene isomers formed by direct CN addition to pyrene under kinetic control in hydrogen-rich gas at 10 K and discuss constraints on the H/CN ratio for PAHs in TMC-1., Comment: Submitted version to comply with licensing agreements

Polycyclic aromatic hydrocarbons (PAHs) are expected to be the most abundant class of organic molecules in space. Their interstellar lifecycle is not well understood, and progress is hampered by difficulties detecting individual PAH molecules. Here, we present the discovery of CN-functionalized pyrene, a 4-ring PAH, in the dense cloud TMC-1 using the 100-m Green Bank Telescope. We derive an abundance of 1-cyanopyrene of ~1.52 x $10^{12}$ cm$^{-2}$, and from this estimate that the un-substituted pyrene accounts for up to ~0.03-0.3% of the carbon budget in the dense interstellar medium which trace the birth sites of stars and planets. The presence of pyrene in this cold (~10 K) molecular cloud agrees with its recent measurement in asteroid Ryugu where isotopic clumping suggest a cold, interstellar origin. The direct link to the birth site of our solar system is strengthened when we consider the solid state pyrene content in the pre-stellar materials compared to comets, which represent the most pristine material in the solar system. We estimate that solid state pyrene can account for 1% of the carbon within comets carried by this one single organic molecule. The abundance indicates pyrene is an "island of stability" in interstellar PAH chemistry and suggests a potential cold molecular cloud origin of the carbon carried by PAHs that is supplied to forming planetary systems, including habitable worlds such as our own., Comment: Version of manuscript revised to comply with licensing requirements

We used new high spectral resolution observations of propynal (HCCCHO) towards TMC-1 and in the laboratory to update the spectral line catalog available for transitions of HCCCHO - specifically at frequencies lower than 30 GHz which were previously discrepant in a publicly available catalog. The observed astronomical frequencies provided high enough spectral resolution that, when combined with high-resolution (~2 kHz) measurements taken in the laboratory, a new, consistent fit to both the laboratory and astronomical data was achieved. Now with a nearly exact (<1 kHz) frequency match to the J=2-1 and 3-2 transitions in the astronomical data, using a Markov chain Monte Carlo (MCMC) analysis, a best fit to the total HCCCHO column density of 7.28+4.08/-1.94 x 10^12 cm^-2 was found with a surprisingly low excitation temperature of just over 3 K. This column density is around a factor of 5 times larger than reported in previous studies. Finally, this work highlights that care is needed when using publicly available spectral catalogs to characterize astronomical spectra. The availability of these catalogs is essential to the success of modern astronomical facilities and will only become more important as the next generation of facilities come online., Comment: 14 pages, 5 figures, 5 Tables, 1 Appendix

Recent detections of aromatic species in dark molecular clouds suggest formation pathways may be efficient at very low temperatures and pressures, yet current astrochemical models are unable to account for their derived abundances, which can often deviate from model predictions by several orders of magnitude. The propargyl radical, a highly abundant species in the dark molecular cloud TMC- 1, is an important aromatic precursor in combustion flames and possibly interstellar environments. We performed astrochemical modeling of TMC-1 using the three-phase gas-grain code NAUTILUS and an updated chemical network, focused on refining the chemistry of the propargyl radical and related species. The abundance of the propargyl radical has been increased by half an order of magnitude compared to the previous GOTHAM network. This brings it closer in line with observations, but it remains underestimated by two orders of magnitude compared to its observed value. Predicted abundances for the chemically related C4H3N isomers within an order of magnitude of observed values corroborate the high efficiency of CN addition to closed-shell hydrocarbons under dark molecular cloud conditions. The results of our modeling provide insight into the chemical processes of the propargyl radical in dark molecular clouds and highlight the importance of resonance-stabilized radicals in PAH formation., Comment: 31 pages and 17 figures (including the appendix), accepted for publication in The Astrophysical Journal

We report the detection of the lowest energy conformer of $E$-1-cyano-1,3-butadiene ($E$-1-C$_4$H$_5$CN), a linear isomer of pyridine, using the fourth data reduction of the GOTHAM deep spectral survey toward TMC-1 with the 100 m Green Bank Telescope. We performed velocity stacking and matched filter analyses using Markov chain Monte Carlo simulations and find evidence for the presence of this molecule at the 5.1$\sigma$ level. We derive a total column density of $3.8^{+1.0}_{-0.9}\times 10^{10}$ cm$^{-2}$, which is predominantly found toward two of the four velocity components we observe toward TMC-1. We use this molecule as a proxy for constraining the gas-phase abundance of the apolar hydrocarbon 1,3-butadiene. Based on the three-phase astrochemical modeling code NAUTILUS and an expanded chemical network, our model underestimates the abundance of cyano-1,3-butadiene by a factor of 19, with a peak column density of $2.34 \times 10^{10}\ \mathrm{cm}^{-2}$ for 1,3-butadiene. Compared to the modeling results obtained in previous GOTHAM analyses, the abundance of 1,3-butadiene is increased by about two orders of magnitude. Despite this increase, the modeled abundances of aromatic species do not appear to change and remain underestimated by 1--4 orders of magnitude. Meanwhile, the abundances of the five-membered ring molecules increase proportionally with 1,3-butadiene by two orders of magnitudes. We discuss implications for bottom-up formation routes to aromatic and polycyclic aromatic molecules.

Increasing attention has been drawn to the misuse of statistical methods over recent years, with particular concern about the prevalence of practices such as poor experimental design, cherry-picking and inadequate reporting. These failures are largely unintentional and no more common in ecology than in other scientific disciplines, with many of them easily remedied given the right guidance. Originating from a discussion at the 2020 International Statistical Ecology Conference, we show how ecologists can build their research following four guiding principles for impactful statistical research practices: 1. Define a focused research question, then plan sampling and analysis to answer it; 2. Develop a model that accounts for the distribution and dependence of your data; 3. Emphasise effect sizes to replace statistical significance with ecological relevance; 4. Report your methods and findings in sufficient detail so that your research is valid and reproducible. Listed in approximate order of importance, these principles provide a framework for experimental design and reporting that guards against unsound practices. Starting with a well-defined research question allows researchers to create an efficient study to answer it, and guards against poor research practices that lead to false positives and poor replicability. Correct and appropriate statistical models give sound conclusions, good reporting practices and a focus on ecological relevance make results impactful and replicable. Illustrated with an example from a recent study into the impact of disturbance on upland swamps, this paper explains the rationale for the selection and use of effective statistical practices and provides practical guidance for ecologists seeking to improve their use of statistical methods., Comment: 19 pages, 2 figures

Using data from the GOTHAM (GBT Observations of TMC-1: Hunting for Aromatic Molecules) survey, we report the first astronomical detection of the C10H- anion. The astronomical observations also provided the necessary data to refine the spectroscopic parameters of C10H-. From the velocity stacked data and the matched filter response, C10H- is detected at >9{\sigma} confidence level at a column density of 4.04e11 cm-2. A dedicated search for the C10H radical was also conducted towards TMC-1. In this case, the stacked molecular emission of C10H was detected at a ~3.2{\sigma} confidence interval at a column density of 2.02e11 cm-2. However, since the determined confidence level is currently <5{\sigma}, we consider the identification of C10H as tentative. The full GOTHAM dataset was also used to better characterize the physical parameters including column density, excitation temperature, linewidth, and source size for the C4H, C6H and C8H radicals and their respective anions, and the measured column densities were compared to the predictions from a gas/grain chemical formation model and from a machine learning analysis. Given the measured values, the C10H-/C10H column density ratio is ~2.0 - the highest value measured between an anion and neutral species to date. Such a high ratio is at odds with current theories for interstellar anion chemistry. For the radical species, both models can reproduce the measured abundances found from the survey; however, the machine learning analysis matches the detected anion abundances much better than the gas/grain chemical model, suggesting that the current understanding of the formation chemistry of molecular anions is still highly uncertain., Comment: 38 Pages, 24 Figures, 12 Tables, 8 Appendices

We present laboratory rotational spectroscopy of five isomers of cyanoindene (2-, 4-, 5-, 6-, and 7-cyanoindene) using a cavity Fourier-transform microwave spectrometer operating between 6-40 GHz. Based on these measurements, we report the detection of 2-cyanoindene (1H-indene-2-carbonitrile; 2-C$_9$H$_7$CN) in GOTHAM line survey observations of the dark molecular cloud TMC-1 using the Green Bank Telescope at centimeter wavelengths. Using a combination of Markov Chain Monte Carlo (MCMC), spectral stacking, and matched filtering techniques, we find evidence for the presence of this molecule at the 6.3$\sigma$ level. This provides the first direct observation of the ratio of a cyano-substituted polycyclic aromatic hydrocarbon (PAH) to its pure hydrocarbon counterpart, in this case indene, in the same source. We discuss the possible formation chemistry of this species, including why we have only detected one of the isomers in TMC-1. We then examine the overall hydrocarbon:CN-substituted ratio across this and other simpler species, as well as compare to those ratios predicted by astrochemical models. We conclude that while astrochemical models are not yet sufficiently accurate to reproduce absolute abundances of these species, they do a good job at predicting the ratios of hydrocarbon:CN-substituted species, further solidifying -CN tagged species as excellent proxies for their fully-symmetric counterparts., Comment: Accepted in ApJL

An optical microscopic examination of thinly cut stained tissue on glass slides prepared from a FFPE tissue blocks is the gold standard for tissue diagnostics. In addition, the diagnostic abilities and expertise of any pathologist is dependent on their direct experience with common as well as rarer variant morphologies. Recently, deep learning approaches have been used to successfully show a high level of accuracy for such tasks. However, obtaining expert-level annotated images is an expensive and time-consuming task and artificially synthesized histological images can prove greatly beneficial. Here, we present an approach to not only generate histological images that reproduce the diagnostic morphologic features of common disease but also provide a user ability to generate new and rare morphologies. Our approach involves developing a generative adversarial network model that synthesizes pathology images constrained by class labels. We investigated the ability of this framework in synthesizing realistic prostate and colon tissue images and assessed the utility of these images in augmenting diagnostic ability of machine learning methods as well as their usability by a panel of experienced anatomic pathologists. Synthetic data generated by our framework performed similar to real data in training a deep learning model for diagnosis. Pathologists were not able to distinguish between real and synthetic images and showed a similar level of inter-observer agreement for prostate cancer grading. We extended the approach to significantly more complex images from colon biopsies and showed that the complex microenvironment in such tissues can also be reproduced. Finally, we present the ability for a user to generate deepfake histological images via a simple markup of sematic labels.

We report a systematic study of all known methyl carbon chains toward TMC-1 using the second data release of the GOTHAM survey, as well as a search for larger species. Using Markov-Chain Monte Carlo simulations and spectral line stacking of over 30 rotational transitions, we report statistically significant emission from methylcyanotriacetylene (CH$_3$C$_7$N) at a confidence level of 4.6$\sigma$, and use it to derive a column density of ${\sim}$10$^{11}$ cm$^{-2}$. We also searched for the related species, methyltetraacetylene (CH$_3$C$_8$H), and place upper limits on the column density of this molecule. By carrying out the above statistical analyses for all other previously detected methyl-terminated carbon chains that have emission lines in our survey, we assess the abundances, excitation conditions, and formation chemistry of methylpolyynes (CH3C$_{2n}$H) and methylcyanopolyynes (CH3C$_{2n-1}$N) in TMC-1, and compare those with predictions from a chemical model. Based on our observed trends in column density and relative populations of the A and E nuclear spin isomers, we find that the methylpolyynes and methylcyanopolyynes families exhibit stark differences from one another, pointing to separate interstellar formation pathways, which is confirmed through gas-grain chemical modeling with nautilus., Comment: 15 pages, 7 figures. Accepted for publication in ApJ