Tetrabenzoporphyrin and -mono-, - Cis -di- and tetrabenzotriazaporphyrin derivatives: Electrochemical and spectroscopic implications of meso CH Group replacement with nitrogen

Nonperipherally hexyl-substituted metal-free tetrabenzoporphyrin (2H-TBP, 1a) tetrabenzomonoazaporphyrin (2H-TBMAP, 2a), tetrabenzo-cis-diazaporphyrin (2H-TBDAP, 3a), tetrabenzotriazaporphyrin (2H-TBTAP, 4a), and phthalocyanine (2H-Pc, 5a), as well as their copper complexes (1b-5b), were synthesized. As the number of meso nitrogen atoms increases from zero to four, Îmax of the Q-band absorption peak becomes red-shifted by almost 100 nm, and extinction coefficients increased at least threefold. Simultaneously the blue-shifted Soret (UV) band substantially decreased in intensity. These changes were related to the relative electron-density of each macrocycle expressed as the group electronegativity sum of all meso N and CH atom groups, âχR. X-ray photoelectron spectroscopy differentiated between the three different types of macrocyclic nitrogen atoms (the Ninner, (NH)inner, and Nmeso) in the metal-free complexes. Binding energies of the Nmeso and Ninner,Cu atoms in copper chelates could not be resolved. Copper insertion lowered especially the cathodic redox potentials, while all four observed redox processes occurred at larger potentials as the number of meso nitrogens increased. Computational chemical methods using density functional theory confirmed 1b to exhibit a Cu(II) reduction prior to ring-based reductions, while for 2b, Cu(II) reduction is the first reductive step only if the nonperipheral substituents are hydrogen. When they are methyl groups, it is the second reduction process; when they are ethyl, propyl, or hexyl, it becomes the third reductive process. Spectro-electrochemical measurements showed redox processes were associated with a substantial change in intensity of at least two main absorbances (the Q and Soret bands) in the UV spectra of these compounds

Genome assembly and population genomic analysis provide insights into the evolution of modern sweet corn.

Sweet corn is one of the most important vegetables in the United States and Canada. Here, we present a de novo assembly of a sweet corn inbred line Ia453 with the mutated shrunken2-reference allele (Ia453-sh2). This mutation accumulates more sugar and is present in most commercial hybrids developed for the processing and fresh markets. The ten pseudochromosomes cover 92% of the total assembly and 99% of the estimated genome size, with a scaffold N50 of 222.2 Mb. This reference genome completely assembles the large structural variation that created the mutant sh2-R allele. Furthermore, comparative genomics analysis with six field corn genomes highlights differences in single-nucleotide polymorphisms, structural variations, and transposon composition. Phylogenetic analysis of 5,381 diverse maize and teosinte accessions reveals genetic relationships between sweet corn and other types of maize. Our results show evidence for a common origin in northern Mexico for modern sweet corn in the U.S. Finally, population genomic analysis identifies regions of the genome under selection and candidate genes associated with sweet corn traits, such as early flowering, endosperm composition, plant and tassel architecture, and kernel row number. Our study provides a high-quality reference-genome sequence to facilitate comparative genomics, functional studies, and genomic-assisted breeding for sweet corn

Allele specific repair of splicing mutations in cystic fibrosis through AsCas12a genome editing.

Funder: Fondazione Fibrosi Cistica - FFC#1/2017Cystic fibrosis (CF) is an autosomal recessive disease caused by mutations in the CFTR gene. The 3272-26A>G and 3849+10kbC>T CFTR mutations alter the correct splicing of the CFTR gene, generating new acceptor and donor splice sites respectively. Here we develop a genome editing approach to permanently correct these genetic defects, using a single crRNA and the Acidaminococcus sp. BV3L6, AsCas12a. This genetic repair strategy is highly precise, showing very strong discrimination between the wild-type and mutant sequence and a complete absence of detectable off-targets. The efficacy of this gene correction strategy is verified in intestinal organoids and airway epithelial cells derived from CF patients carrying the 3272-26A>G or 3849+10kbC>T mutations, showing efficient repair and complete functional recovery of the CFTR channel. These results demonstrate that allele-specific genome editing with AsCas12a can correct aberrant CFTR splicing mutations, paving the way for a permanent splicing correction in genetic diseases

Impact of instrument and data characteristics in the interferometric reconstruction of the 21 cm power spectrum

Combining the visibilities measured by an interferometer to form a cosmological power spectrum is a complicated process. In a delay-based analysis, the mapping between instrumental and cosmological space is not a one-to-one relation. Instead, neighbouring modes contribute to the power measured at one point, with their respective contributions encoded in the window functions. To better understand the power measured by an interferometer, we assess the impact of instrument characteristics and analysis choices on these window functions. Focusing on the Hydrogen Epoch of Reionization Array (HERA) as a case study, we find that long-baseline observations correspond to enhanced low-k tails of the window functions, which facilitate foreground leakage, whilst an informed choice of bandwidth and frequency taper can reduce said tails. With simple test cases and realistic simulations, we show that, apart from tracing mode mixing, the window functions help accurately reconstruct the power spectrum estimator of simulated visibilities. The window functions depend strongly on the beam chromaticity and less on its spatial structure – a Gaussian approximation, ignoring side lobes, is sufficient. Finally, we investigate the potential of asymmetric window functions, down-weighting the contribution of low-k power to avoid foreground leakage. The window functions presented here correspond to the latest HERA upper limits for the full Phase I data. They allow an accurate reconstruction of the power spectrum measured by the instrument and will be used in future analyses to confront theoretical models and data directly in cylindrical space

Characterization of inpaint residuals in interferometric measurements of the epoch of reionization

To mitigate the effects of Radio Frequency Interference (RFI) on the data analysis pipelines of 21 cm interferometric instruments, numerous inpaint techniques have been developed. In this paper, we examine the qualitative and quantitative errors introduced into the visibilities and power spectrum due to inpainting. We perform our analysis on simulated data as well as real data from the Hydrogen Epoch of Reionization Array (HERA) Phase 1 upper limits. We also introduce a convolutional neural network that is capable of inpainting RFI corrupted data. We train our network on simulated data and show that our network is capable of inpainting real data without requiring to be retrained. We find that techniques that incorporate high wavenumbers in delay space in their modelling are best suited for inpainting over narrowband RFI. We show that with our fiducial parameters discrete prolate spheroidal sequences (DPSS) and CLEAN provide the best performance for intermittent RFI while Gaussian progress regression (GPR) and least squares spectral analysis (LSSA) provide the best performance for larger RFI gaps. However, we caution that these qualitative conclusions are sensitive to the chosen hyperparameters of each inpainting technique. We show that all inpainting techniques reliably reproduce foreground dominated modes in the power spectrum. Since the inpainting techniques should not be capable of reproducing noise realizations, we find that the largest errors occur in the noise dominated delay modes. We show that as the noise level of the data comes down, CLEAN and DPSS are most capable of reproducing the fine frequency structure in the visibilities

Identification of DHX9 as a cell cycle regulated nucleolar recruitment factor for CIZ1

CIP1-interacting zinc finger protein 1 (CIZ1) is a nuclear matrix associated protein that facilitates a number of nuclear functions including initiation of DNA replication, epigenetic maintenance and associates with the inactive X-chromosome. Here, to gain more insight into the protein networks that underpin this diverse functionality, molecular panning and mass spectrometry are used to identify protein interaction partners of CIZ1, and CIZ1 replication domain (CIZ1-RD). STRING analysis of CIZ1 interaction partners identified 2 functional clusters: ribosomal subunits and nucleolar proteins including the DEAD box helicases, DHX9, DDX5 and DDX17. DHX9 shares common functions with CIZ1, including interaction with XIST long-non-coding RNA, epigenetic maintenance and regulation of DNA replication. Functional characterisation of the CIZ1-DHX9 complex showed that CIZ1-DHX9 interact in vitro and dynamically colocalise within the nucleolus from early to mid S-phase. CIZ1-DHX9 nucleolar colocalisation is dependent upon RNA polymerase I activity and is abolished by depletion of DHX9. In addition, depletion of DHX9 reduced cell cycle progression from G1 to S-phase in mouse fibroblasts. The data suggest that DHX9-CIZ1 are required for efficient cell cycle progression at the G1/S transition and that nucleolar recruitment is integral to their mechanism of action

Improved Constraints on the 21 cm EoR Power Spectrum and the X-Ray Heating of the IGM with HERA Phase I Observations

We report the most sensitive upper limits to date on the 21 cm epoch of reionization power spectrum using 94 nights of observing with Phase I of the Hydrogen Epoch of Reionization Array (HERA). Using similar analysis techniques as in previously reported limits, we find at 95% confidence that Δ2(k = 0.34 h Mpc−1) ≤ 457 mK2 at z = 7.9 and that Δ2(k = 0.36 h Mpc−1) ≤ 3496 mK2 at z = 10.4, an improvement by a factor of 2.1 and 2.6, respectively. These limits are mostly consistent with thermal noise over a wide range of k after our data quality cuts, despite performing a relatively conservative analysis designed to minimize signal loss. Our results are validated with both statistical tests on the data and end-to-end pipeline simulations. We also report updated constraints on the astrophysics of reionization and the cosmic dawn. Using multiple independent modeling and inference techniques previously employed by HERA Collaboration, we find that the intergalactic medium must have been heated above the adiabatic cooling limit at least as early as z = 10.4, ruling out a broad set of so-called “cold reionization” scenarios. If this heating is due to high-mass X-ray binaries during the cosmic dawn, as is generally believed, our result’s 99% credible interval excludes the local relationship between soft X-ray luminosity and star formation and thus requires heating driven by evolved low-metallicity stars

Bayesian jackknife tests with a small number of subsets: Application to HERA 21cm power spectrum upper limits

We present a Bayesian jackknife test for assessing the probability that a data set contains biased subsets, and, if so, which of the subsets are likely to be biased. The test can be used to assess the presence and likely source of statistical tension between different measurements of the same quantities in an automated manner. Under certain broadly applicable assumptions, the test is analytically tractable. We also provide an open-source code, CHIBORG, that performs both analytic and numerical computations of the test on general Gaussian-distributed data. After exploring the information theoretical aspects of the test and its performance with an array of simulations, we apply it to data from the Hydrogen Epoch of Reionization Array (HERA) to assess whether different sub-seasons of observing can justifiably be combined to produce a deeper 21 cm power spectrum upper limit. We find that, with a handful of exceptions, the HERA data in question are statistically consistent and this decision is justified. We conclude by pointing out the wide applicability of this test, including to CMB experiments and the H0 tension

Characterization Of Inpaint Residuals In Interferometric Measurements of the Epoch Of Reionization

Radio Frequency Interference (RFI) is one of the systematic challenges preventing 21cm interferometric instruments from detecting the Epoch of Reionization. To mitigate the effects of RFI on data analysis pipelines, numerous inpaint techniques have been developed to restore RFI corrupted data. We examine the qualitative and quantitative errors introduced into the visibilities and power spectrum due to inpainting. We perform our analysis on simulated data as well as real data from the Hydrogen Epoch of Reionization Array (HERA) Phase 1 upper limits. We also introduce a convolutional neural network that capable of inpainting RFI corrupted data in interferometric instruments. We train our network on simulated data and show that our network is capable at inpainting real data without requiring to be retrained. We find that techniques that incorporate high wavenumbers in delay space in their modeling are best suited for inpainting over narrowband RFI. We also show that with our fiducial parameters Discrete Prolate Spheroidal Sequences (DPSS) and CLEAN provide the best performance for intermittent ``narrowband'' RFI while Gaussian Progress Regression (GPR) and Least Squares Spectral Analysis (LSSA) provide the best performance for larger RFI gaps. However we caution that these qualitative conclusions are sensitive to the chosen hyperparameters of each inpainting technique. We find these results to be consistent in both simulated and real visibilities. We show that all inpainting techniques reliably reproduce foreground dominated modes in the power spectrum. Since the inpainting techniques should not be capable of reproducing noise realizations, we find that the largest errors occur in the noise dominated delay modes. We show that in the future, as the noise level of the data comes down, CLEAN and DPSS are most capable of reproducing the fine frequency structure in the visibilities of HERA data.Comment: 26 pages, 18 figure