Preserved records of tooth–bone interactions, known as tooth marks, can yield a wealth of information regarding organismal behavior and ecology. For this reason, workers in a wide range of disciplines, but particularly paleontology, have inspected and interpreted these features for decades. Although previous studies have gleaned invaluable insights, they have also described tooth marks using terminological frameworks that have been incompletely defined, have incorporated behavioral hypotheses in definitions, and/or have been inconsistently applied. To address these problems, we introduce the category-modifier (CM) system, the first system to both sort tooth marks into clearly defined main categories and use descriptive modifiers to characterize their appearance more precisely. The CM system is designed to apply to a wide range of vertebrates, to enable comparisons across disciplines and studies, and to help researchers keep their investigations into behavioral hypotheses free of circular reasoning.

The interaction of relativistically intense lasers with opaque targets represents a highly non-linear, multi-dimensional parameter space. This limits the utility of sequential 1D scanning of experimental parameters for the optimization of secondary radiation, although to-date this has been the accepted methodology due to low data acquisition rates. High repetition-rate (HRR) lasers augmented by machine learning present a valuable opportunity for efficient source optimization. Here, an automated, HRR-compatible system produced high-fidelity parameter scans, revealing the influence of laser intensity on target pre-heating and proton generation. A closed-loop Bayesian optimization of maximum proton energy, through control of the laser wavefront and target position, produced proton beams with equivalent maximum energy to manually optimized laser pulses but using only 60% of the laser energy. This demonstration of automated optimization of laser-driven proton beams is a crucial step towards deeper physical insight and the construction of future radiation sources.

We present the development and characterization of a high-stability, multi-material, multi-thickness tape-drive target for laser-driven acceleration at repetition rates of up to 100 Hz. The tape surface position was measured to be stable on the sub-micrometre scale, compatible with the high-numerical aperture focusing geometries required to achieve relativistic intensity interactions with the pulse energy available in current multi-Hz and near-future higher repetition-rate lasers ($>$kHz). Long-term drift was characterized at 100 Hz demonstrating suitability for operation over extended periods. The target was continuously operated at up to 5 Hz in a recent experiment for 70,000 shots without intervention by the experimental team, with the exception of tape replacement, producing the largest data-set of relativistically intense laser–solid foil measurements to date. This tape drive provides robust targetry for the generation and study of high-repetition-rate ion beams using next-generation high-power laser systems, also enabling wider applications of laser-driven proton sources.

The evolution of resistance to multiple herbicides in Palmer amaranth is a major challenge for its management. In this study, a Palmer amaranth population from Hutchinson, Kansas (HMR), was characterized for resistance to inhibitors of photosystem II (PSII) (e.g., atrazine), acetolactate synthase (ALS) (e.g., chlorsulfuron), and EPSP synthase (EPSPS) (e.g., glyphosate), and this resistance was investigated. About 100 HMR plants were treated with field-recommended doses (1×) of atrazine, chlorsulfuron, and glyphosate, separately along with Hutchinson multiple-herbicide (atrazine, chlorsulfuron, and glyphosate)–susceptible (HMS) Palmer amaranth as control. The mechanism of resistance to these herbicides was investigated by sequencing or amplifying the psbA, ALS, and EPSPS genes, the molecular targets of atrazine, chlorsulfuron, and glyphosate, respectively. Fifty-two percent of plants survived a 1× (2,240 g ai ha−1) atrazine application with no known psbA gene mutation, indicating the predominance of a non–target site resistance mechanism to this herbicide. Forty-two percent of plants survived a 1× (18 g ai ha−1) dose of chlorsulfuron with proline197serine, proline197threonine, proline197alanine, and proline197asparagine, or tryptophan574leucine mutations in the ALS gene. About 40% of the plants survived a 1× (840 g ae ha−1) dose of glyphosate with no known mutations in the EPSPS gene. Quantitative PCR results revealed increased EPSPS copy number (50 to 140) as the mechanism of glyphosate resistance in the survivors. The most important finding of this study was the evolution of resistance to at least two sites of action (SOAs) (~50% of plants) and to all three herbicides due to target site as well as non–target site mechanisms. The high incidence of individual plants with resistance to multiple SOAs poses a challenge for effective management of this weed.

Background: The zona incerta (ZI) is a small structure in the deep brain first identified by Auguste Forel for which robust in vivo visualization has remained elusive. The increased inherent signal from ultra-high field (7-Tesla or greater; 7T) magnetic resonance imaging (MRI) presents an opportunity to see structures not previously visible. In this study, we investigated the possibility of using quantitative T1 mapping at 7T to visualize the ZI region. Methods: We recruited healthy participants (N=32) and patients being considered for deep brain stimulation therapy as part of a prospective imaging study at 7T. Computational methods were used to process and fuse images to produce a high-resolution group average from which ZI anatomy could be delineated. Results: We pooled 7T data using image fusion methods and found that the contrast from quantitative T1 mapping was strikingly similar to classic histological staining, permitting facile identification of the ZI and nearby structures in reference to conventional stereotactic atlases. Conclusions: Using computational neuroimaging techniques, we demonstrate for the first time that the ZI is visible in vivo. Furthermore, we determined that this nuclear region can be decoupled from surrounding fibre pathways. This work paves the way for more accurate patient-specific optimization of deep brain targets for neuromodulation.

Fe deficiency is relatively common in pregnancy and has both short- and long-term consequences. However, little is known about the effect on the metabolism of other micronutrients. A total of fifty-four female rats were fed control (50 mg Fe/kg) or Fe-deficient diets (7·5 mg/kg) before and during pregnancy. Maternal liver, placenta and fetal liver were collected at day 21 of pregnancy for Cu and Zn analysis and to measure expression of the major genes of Cu and Zn metabolism. Cu levels increased in the maternal liver (P=0·002) and placenta (P=0·018) of Fe-deficient rats. Zn increased (P<0·0001) and Cu decreased (P=0·006) in the fetal liver. Hepatic expression of the Cu chaperones antioxidant 1 Cu chaperone (P=0·042) and cytochrome c oxidase Cu chaperone (COX17, P=0·020) decreased in the Fe-deficient dams, while the expression of the genes of Zn metabolism was unaltered. In the placenta, Fe deficiency reduced the expression of the chaperone for superoxide dismutase 1, Cu chaperone for superoxide dismutase (P=0·030), ceruloplasmin (P=0·042) and Zn transport genes, ZRT/IRT-like protein 4 (ZIP4, P=0·047) and Zn transporter 1 (ZnT1, P=0·012). In fetal liver, Fe deficiency increased COX17 (P=0·020), ZRT/IRT-like protein 14 (P=0·036) and ZnT1 (P=0·0003) and decreased ZIP4 (P=0·004). The results demonstrate that Fe deficiency during pregnancy has opposite effects on Cu and Zn levels in the fetal liver. This may, in turn, alter metabolism of these nutrients, with consequences for development in the fetus and the neonate.