High-speed electrochemical imaging

The design, development, and application of high-speed scanning electrochemical probe microscopy is reported. The approach allows the acquisition of a series of high-resolution images (typically 1000 pixels μm–2) at rates approaching 4 seconds per frame, while collecting up to 8000 image pixels per second, about 1000 times faster than typical imaging speeds used up to now. The focus is on scanning electrochemical cell microscopy (SECCM), but the principles and practicalities are applicable to many electrochemical imaging methods. The versatility of the high-speed scan concept is demonstrated at a variety of substrates, including imaging the electroactivity of a patterned self-assembled monolayer on gold, visualization of chemical reactions occurring at single wall carbon nanotubes, and probing nanoscale electrocatalysts for water splitting. These studies provide movies of spatial variations of electrochemical fluxes as a function of potential and a platform for the further development of high speed scanning with other electrochemical imaging techniques

Electrochemical and Photovoltaic Properties of Electropolymerized Poly(thienyl-silole)s

Electrochemical and photoelectrochemical properties were studied of a series of donor−acceptor materials based on polythiophene modified with silole moieties. The materials were prepared by electrochemical anodic polymerization of 2,5-bis([2,2′-bithiophen]-5-yl)-1,1-dimethyl-3,4-diphenylsilole and 2,5-bis([2,2′-terthiophen]-5-yl)-1,1-dimethyl-3,4-diphenylsilole, as well as copolymerization of these monomers with 2,2′-bithiophene. Photocurrent measurements showed that introduction of silole resulted in a considerable enhancement of the photovoltaic properties of silole-containing materials and especially the fill factor. However, as demonstrated by Mott−Schottky measurements, electropolymerized silole-containing materials showed a substantial degree of disorder and high density of states in the midgap, which negatively affected their photovoltaic properties. Atomic force microscopy (AFM) and phase imaging revealed the presence of phase segregation and heterogeneity of the silole-containing materials. Interestingly, introduction of siloles suppressed the cathodic (n-type) doping typical for polythiophenes. This work demonstrates that siloles show great promise as electron-acceptor groups for all-organic solar cells; however, further work is required to optimize the properties and performance of poly(thienylsilole)-based materials

Redistribution of Nickel Ions Embedded within Indium Phosphide Via Low Energy Dual Ion Implantations

Transition-metal doped Indium Phosphide (InP) has been studied over several decades for utilization in optoelectronics applications. Recently, interesting magnetic properties have been reported for metal clusters formed at different depths surrounded by a high quality InP lattice. In this work, we have reported accumulation of Ni atoms at various depths in InP via implantation of Ni- followed by H– and subsequently thermal annealing. Prior to the ion implantations, the ion implant depth profile was simulated using an ion-solid interaction code SDTrimSP, incorporating dynamic changes in the target matrix during ion implantation. Initially, 50 keV Ni- ions are implanted with a fluence of 2 × 1015 atoms cm-2, with a simulated peak deposition profile approximately 42 nm from the surface. 50 keV H- ions are then implanted with a fluence of 1.5 × 1016 atoms cm-2. The simulation result indicates that the H- creates damages with a peak defect center ~400 nm below the sample surface. The sample has been annealed at 50°C in an Ar rich environment for approximately 1hr. During the annealing, H vacates the lattice, and the formed nano-cavities act as trapping sites and a gettering effect for Ni diffusion into the substrate. The distribution of Ni atoms in InP samples are estimated by utilizing Rutherford Backscattering Spectrometry and X-ray Photoelectron Spectroscopy based depth profiling while sputtering the sample with Ar-ion beams. In the sample annealed after H implantation, the Ni was found to migrate to deeper depths of 125 nm than the initial end of range of 70 nm

Phase I, Dose-Escalation, Two-Part Trial of the PARP Inhibitor Talazoparib in Patients with Advanced Germline BRCA1/2 Mutations and Selected Sporadic Cancers

Talazoparib inhibits PARP catalytic activity, trapping PARP1 on damaged DNA and causing cell death in BRCA1/2-mutated cells. We evaluated talazoparib therapy in this two-part, phase I, first-in-human trial. Antitumor activity, MTD, pharmacokinetics, and pharmacodynamics of once-daily talazoparib were determined in an open-label, multicenter, dose-escalation study (NCT01286987). The MTD was 1.0 mg/day, with an elimination half-life of 50 hours. Treatment-related adverse events included fatigue (26/71 patients; 37%) and anemia (25/71 patients; 35%). Grade 3 to 4 adverse events included anemia (17/71 patients; 24%) and thrombocytopenia (13/71 patients; 18%). Sustained PARP inhibition was observed at doses ≥0.60 mg/day. At 1.0 mg/day, confirmed responses were observed in 7 of 14 (50%) and 5 of 12 (42%) patients with BRCA mutation–associated breast and ovarian cancers, respectively, and in patients with pancreatic and small cell lung cancer. Talazoparib demonstrated single-agent antitumor activity and was well tolerated in patients at the recommended dose of 1.0 mg/day

Estimating yield-contributing physiological parameters of cotton using UAV-based imagery

Lint yield in cotton is governed by light intercepted by the canopy (IPAR), radiation use efficiency (RUE), and harvest index (HI). However, the conventional methods of measuring these yield-governing physiological parameters are labor-intensive, time-consuming and requires destructive sampling. This study aimed to explore the use of low-cost and high-resolution UAV-based RGB and multispectral imagery 1) to estimate fraction of IPAR (IPARf), RUE, and biomass throughout the season, 2) to estimate lint yield using the cotton fiber index (CFI), and 3) to determine the potential use of biomass and lint yield models for estimating cotton HI. An experiment was conducted during the 2021 and 2022 growing seasons in Tifton, Georgia, USA in randomized complete block design with five different nitrogen treatments. Different nitrogen treatments were applied to generate substantial variability in canopy development and yield. UAV imagery was collected bi-weekly along with light interception and biomass measurements throughout the season, and 20 different vegetation indices (VIs) were computed from the imagery. Generalized linear regression was performed to develop models using VIs and growing degree days (GDDs). The IPARf models had R2 values ranging from 0.66 to 0.90, and models based on RVI and RECI explained the highest variation (93%) in IPARf during cross-validation. Similarly, cotton above-ground biomass was best estimated by models from MSAVI and OSAVI. Estimation of RUE using actual biomass measurement and RVI-based IPARf model was able to explain 84% of variation in RUE. CFI from UAV-based RGB imagery had strong relationship (R2 = 0.69) with machine harvested lint yield. The estimated HI from CFI-based lint yield and MSAVI-based biomass models was able to explain 40 to 49% of variation in measured HI for the 2022 growing season. The models developed to estimate the yield-contributing physiological parameters in cotton showed low to strong performance, with IPARf and above-ground biomass having greater prediction accuracy. Future studies on accurate estimation of lint yield is suggested for precise cotton HI prediction. This study is the first attempt of its kind and the results can be used to expand and improve research on predicting functional yield drivers of cotton

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

The case for the continued use of the genus name Mimulus for all monkeyflowers

The genus Mimulus is a well-studied group of plant species, which has for decades allowed researchers to address a wide array of fundamental questions in biology (Wu & al. 2008; Twyford & al. 2015). Linnaeus named the type species of Mimulus (ringens L.), while Darwin (1876) used Mimulus (luteus L.) to answer key research questions. The incredible phenotypic diversity of this group has made it the focus of ecological and evolutionary study since the mid-20th century, initiated by the influential work of Clausen, Keck, and Hiesey as well as their students and collaborators (Clausen & Hiesey 1958; Hiesey & al. 1971, Vickery 1952, 1978). Research has continued on this group of diverse taxa throughout the 20th and into the 21st century (Bradshaw & al. 1995; Schemske & Bradshaw 1999; Wu & al. 2008; Twyford & al. 2015; Yuan 2019), and Mimulus guttatus was one of the first non-model plants to be selected for full genome sequencing (Hellsten & al. 2013). Mimulus has played a key role in advancing our general understanding of the evolution of pollinator shifts (Bradshaw & Schemske 2003; Cooley & al. 2011; Byers & al. 2014), adaptation (Lowry & Willis 2010; Kooyers & al. 2015; Peterson & al. 2016; Ferris & Willis 2018; Troth & al. 2018), speciation (Ramsey & al. 2003; Wright & al. 2013; Sobel & Streisfeld 2015; Zuellig & Sweigart 2018), meiotic drive (Fishman & Saunders 2008), polyploidy (Vallejo-Marín 2012; Vallejo-Marín & al. 2015), range limits (Angert 2009; Sexton et al. 2011; Grossenbacher & al. 2014; Sheth & Angert 2014), circadian rhythms (Greenham & al. 2017), genetic recombination (Hellsten & al. 2013), mating systems (Fenster & Ritland 1994; Dudash & Carr 1998; Brandvain & al. 2014) and developmental biology (Moody & al. 1999; Baker & al. 2011, 2012; Yuan 2019). This combination of a rich history of study coupled with sustained modern research activity is unparalleled among angiosperms. Across many interested parties, the name Mimulus therefore takes on tremendous biological significance and is recognizable not only by botanists, but also by zoologists, horticulturalists, naturalists, and members of the biomedical community. Names associated with a taxonomic group of this prominence should have substantial inertia, and disruptive name changes should be avoided. As members of the Mimulus community, we advocate retaining the genus name Mimulus to describe all monkeyflowers. This is despite recent nomenclature changes that have led to a renaming of most monkeyflower species to other genera.Additional co-authors: Jannice Friedman, Dena L Grossenbacher, Liza M Holeski, Christopher T Ivey, Kathleen M Kay, Vanessa A Koelling, Nicholas J Kooyers, Courtney J Murren, Christopher D Muir, Thomas C Nelson, Megan L Peterson, Joshua R Puzey, Michael C Rotter, Jeffrey R Seemann, Jason P Sexton, Seema N Sheth, Matthew A Streisfeld, Andrea L Sweigart, Alex D Twyford, John H Willis, Kevin M Wright, Carrie A Wu, Yao-Wu Yua

Diversity analysis of cotton (Gossypium hirsutum L.) germplasm using the CottonSNP63K Array

Cotton germplasm resources contain beneficial alleles that can be exploited to develop germplasm adapted to emerging environmental and climate conditions. Accessions and lines have traditionally been characterized based on phenotypes, but phenotypic profiles are limited by the cost, time, and space required to make visual observations and measurements. With advances in molecular genetic methods, genotypic profiles are increasingly able to identify differences among accessions due to the larger number of genetic markers that can be measured. A combination of both methods would greatly enhance our ability to characterize germplasm resources. Recent efforts have culminated in the identification of sufficient SNP markers to establish high-throughput genotyping systems, such as the CottonSNP63K array, which enables a researcher to efficiently analyze large numbers of SNP markers and obtain highly repeatable results. In the current investigation, we have utilized the SNP array for analyzing genetic diversity primarily among cotton cultivars, making comparisons to SSR-based phylogenetic analyses, and identifying loci associated with seed nutritional traits. (Résumé d'auteur