Search

Abstract The use of wildlife imagery in society is highly varied and could contribute to reinforcing national identity. Standard depictions of wildlife include photographs, video, artwork and symbols or icons, including on currency. We investigated the representation of native fauna on 4541 banknotes from 207 countries between 1980 and 2017, to identify geographic hotspots and taxonomic patterns and determine whether threatened and endemic species were more readily represented. Native fauna was depicted on 15.2% of banknotes reviewed (352 unique species) with a strong bias towards terrestrial species (89%) and a dominance of bird and mammal species (83% combined). African banknotes had the highest mammal representation while birds were favoured in South America. Globally, threatened species were commonly depicted on banknotes with 30% of all imagery representing these species. The fauna species depicted on banknotes generally perpetuate existing perceptions about these species (i.e., charismatic species). We recommend several avenues for further investigation to explore relationships between perceived value and wildlife representation. These include longitudinal studies of how representation changes over time, the inclusion of flora and/or coin imagery, identifying species‐specific traits for selected wildlife and examining the decision‐making processes governing wildlife imagery on banknotes. Read the free Plain Language Summary for this article on the Journal blog.

Abstract Background Automated radio telemetry (ART) systems enable high-temporal resolution data collection for species unsuited to satellite-based methods. A challenge of ART systems is estimating the location of radio tagged animals from the radio signals received on multiple antennas within an ART array. Localisation methods for ART systems with omni-directional receivers have undergone rapid development in recent years, with the inclusion of machine learning techniques. However, comparable machine learning methods for ART systems with directional antennas are unavailable, despite their potential for improved accuracy and greater versatility. To address this, we introduce an open-source machine learning-based location fingerprinting method for directional antenna-based ART systems. We compare this method to two alternative localisation approaches. Both alternatives use relative signal strengths recorded among multiple antennas to estimate the signal’s angle of arrival at each receiver. In the ‘biangulation’ approach, the location is estimated by finding the intersection of these angles from two receivers. In contrast, the ‘linear regression’ approach uses a linear regression model to estimate the distance from the receiver along the angle of arrival, providing a location estimate. We evaluate these methods using an ART data set collected for the southern black-throated finch (Poephila cincta cincta), in the Desert Uplands Bioregion of Queensland, Australia. Results The location fingerprinting method performed slightly better than the best performing alternative, the linear regression method, with mean positional errors of 308 m (SE = 17.7) and 335 m (SE = 18.5), respectively. The biangulation method performed substantially worse, with a mean positional error of 550 m (SE = 42.9, median = 540 m). Improved accuracy was observed with shorter distances between transmitters and receivers, higher signal strengths, and a greater number of detecting receivers, suggesting that increasing receiver density improves localisation accuracy, albeit with potential trade-offs in system coverage or cost. Furthermore, shorter pulse intervals of transmitters resulted in greater accuracy, highlighting the trade-offs among battery life, transmitter weight and radiative power. Conclusions The open-source location fingerprinting method offers an improved and versatile localisation approach suitable for a wide variety of ART system designs, addressing the challenge of developing study-specific localisation methods using alternative approaches.

Primary lung carcinoma or lung cancer (LC) is classified into small-cell or non-small-cell (NSCLC) lung carcinoma. Lung squamous cell carcinoma (LSCC) is the second most common subtype of NSCLC responsible for 30% of all LCs, and its survival remains low with only 24% of patients living for five years or longer post-diagnosis primarily due to the advanced stage of tumors at the time of diagnosis. The pathogenesis of LSCC is still poorly understood and has hampered the development of effective diagnostics and therapies. This review highlights the known risk factors, genetic and epigenetic alterations, miRNA biomarkers linked to the development and diagnosis of LSCC and the lack of therapeutic strategies to target specifically LSCC. We will also discuss existing animal models of LSCC including carcinogen induced, transgenic and xenograft mouse models, and their advantages and limitations along with the chemopreventive studies and molecular studies conducted using them. The importance of developing new and improved mouse models will also be discussed that will provide further insights into the initiation and progression of LSCC, and enable the identification of new biomarkers and therapeutic targets.

We present the Ly α Continuum Analysis Network (LyCAN), a convolutional neural network that predicts the unabsorbed quasar continuum within the rest-frame wavelength range of 1040–1600 Å based on the red side of the Ly α emission line (1216–1600 Å). We developed synthetic spectra based on a Gaussian mixture model representation of nonnegative matrix factorization (NMF) coefficients. These coefficients were derived from high-resolution, low-redshift ( z < 0.2) Hubble Space Telescope/Cosmic Origins Spectrograph (COS) quasar spectra. We supplemented this COS-based synthetic sample with an equal number of DESI Year 5 mock spectra. LyCAN performs extremely well on testing sets, achieving a median error in the forest region of 1.5% on the DESI mock sample, 2.0% on the COS-based synthetic sample, and 4.1% on the original COS spectra. LyCAN outperforms principal component analysis (PCA) and NMF-based prediction methods using the same training set by 40% or more. We predict the intrinsic continua of 83,635 DESI Year 1 spectra in the redshift range of 2.1 ≤ z ≤ 4.2 and perform an absolute measurement of the evolution of the effective optical depth. This is the largest sample employed to measure the optical depth evolution to date. We fit a power law of the form $\tau {(z)={\tau }_{0}(1+z)}^{\gamma }$ to our measurements and find τ _0 = (2.46 ± 0.14) × 10 ^−3 and γ = 3.62 ± 0.04. Our results show particular agreement with high-resolution, ground-based observations around z = 2, indicating that LyCAN is able to predict the quasar continuum in the forest region with only spectral information outside the forest.

Highly multiplexed, robotic, fiber-fed spectroscopic surveys are observing tens of millions of stars and galaxies. For many systems, accurate positioning relies on imaging the fibers in the focal plane and feeding that information back to the robotic positioners to correct their positions. Inhomogeneities and turbulence in the air between the focal plane and the imaging camera can affect the measured positions of fibers, limiting the accuracy with which fibers can be placed on targets. For the Dark Energy Spectroscopic Instrument, we dramatically reduced the effect of turbulence on measurements of positioner locations in the focal plane by taking advantage of stationary positioners and the correlation function of the turbulence. We were able to reduce positioning errors from 7.3 to 3.5 μ m, speeding the survey by 1.6% under typical conditions.

We explore the influence of radio-mode feedback on the properties of the cool circumgalactic medium (CGM). To this end, we assemble a statistical sample of approximately 30,000 radio galaxies with background quasars by combining optical spectroscopic measurements of luminous red galaxies and quasars from the year 1 data set of the Dark Energy Spectroscopic Instrument and radio sources from the LOw-Frequency ARray Two-metre Sky Survey (LoTSS) DR2 catalog and the Very Large Array Sky Survey (VLASS) quick-look catalog. Galaxies with similar optical properties but with no radio counterparts in LoTSS and VLASS are selected as the control group. We measure the cool CGM properties of radio galaxies and their control samples traced by Mg ii absorption lines, including covering fraction, rest equivalent width, and gas kinematics. Our results show no significant difference in the properties of gas around radio galaxies and their control sample, indicating that the operating radio-mode feedback of massive galaxies does not produce detectable effects on the properties of the cool CGM. Finally, we show that the CGM of radio galaxies contains a nonnegligible amount of cool gas with approximately 10 ^10 M _⊙ . This abundance can place a stringent constraint on the radio-mode feedback models.

The Dark Energy Spectroscopic Instrument (DESI) completed its 5 month Survey Validation in 2021 May. Spectra of stellar and extragalactic targets from Survey Validation constitute the first major data sample from the DESI survey. This paper describes the public release of those spectra, the catalogs of derived properties, and the intermediate data products. In total, the public release includes good-quality spectral information from 466,447 objects targeted as part of the Milky Way Survey, 428,758 as part of the Bright Galaxy Survey, 227,318 as part of the Luminous Red Galaxy sample, 437,664 as part of the Emission Line Galaxy sample, and 76,079 as part of the Quasar sample. In addition, the release includes spectral information from 137,148 objects that expand the scope beyond the primary samples as part of a series of secondary programs. Here, we describe the spectral data, data quality, data products, Large-Scale Structure science catalogs, access to the data, and references that provide relevant background to using these spectra.

Highly multiplexed, fiber-fed spectroscopy is enabling surveys of millions of stars and galaxies. The performance of these surveys depends on accurately positioning fibers in the focal plane to capture target light. We describe a technique to measure the positioning accuracy of fibers by dithering fibers slightly around their ideal locations. This approach also enables measurement of the total system throughput and point-spread function delivered to the focal plane. We then apply this technique to observations from the Dark Energy Survey Instrument (DESI), and demonstrate that DESI positions fibers to within 0.″08 of their targets (5% of a fiber diameter) and achieves a system throughput within about 7% of expectations.

The Dark Energy Spectroscopic Instrument (DESI) was designed to conduct a survey covering 14,000 deg ^2 over 5 yr to constrain the cosmic expansion history through precise measurements of baryon acoustic oscillations (BAO). The scientific program for DESI was evaluated during a 5 month survey validation (SV) campaign before beginning full operations. This program produced deep spectra of tens of thousands of objects from each of the stellar Milky Way Survey (MWS), Bright Galaxy Survey (BGS), luminous red galaxy (LRG), emission line galaxy (ELG), and quasar target classes. These SV spectra were used to optimize redshift distributions, characterize exposure times, determine calibration procedures, and assess observational overheads for the 5 yr program. In this paper, we present the final target selection algorithms, redshift distributions, and projected cosmology constraints resulting from those studies. We also present a One-Percent Survey conducted at the conclusion of SV covering 140 deg ^2 using the final target selection algorithms with exposures of a depth typical of the main survey. The SV indicates that DESI will be able to complete the full 14,000 deg ^2 program with spectroscopically confirmed targets from the MWS, BGS, LRG, ELG, and quasar programs with total sample sizes of 7.2, 13.8, 7.46, 15.7, and 2.87 million, respectively. These samples will allow exploration of the Milky Way halo, clustering on all scales, and BAO measurements with a statistical precision of 0.28% over the redshift interval z < 1.1, 0.39% over the redshift interval 1.1 < z < 1.9, and 0.46% over the redshift interval 1.9 < z < 3.5.

Abstract Habitat fragmentation and isolation threaten the survival of several wide‐ranging species, such as tigers, through increased risk from diseases, disasters, climate change, and genetic depression. Identification of the habitat most likely to achieve connectivity among protected areas is vital for the long‐term persistence of tigers. We aimed to improve the mapping of potential transfrontier protected area corridors for tigers by connecting sites within the Terai Arc Landscape in Nepal and to those in India, highlighting targeted conservation actions needed along these corridors to maintain long‐term connectivity. We used least‐cost corridor modeling and circuit theory to identify potential corridors and bottlenecks in the study area. The landscape's resistance to tigers' movement was gathered from expert opinions to inform corridor modeling. We identified nine potential tiger corridors in the Terai Arc Landscape—Nepal that aligned strongly with the remaining intact habitats of the Siwalik landscape, which could facilitate tiger movement. Banke‐Bardia and Chitwan‐Parsa‐Valimiki complexes and Lagga‐Bhagga and Khata corridors were identified as high‐priority conservation cores and corridors. While our model exhibited congruence with most established corridors in the landscape, it has identified the need to enhance existing corridors to improve landscape connectivity. Several pinch points posing an increased risk to connectivity were identified. Most of these were located near the protected area boundaries and along the Nepal–India border. The Siwalik landscape holds the key to long‐term connectivity in the study area; however, immediate conservation attention is needed, particularly at pinch points, to secure this connectivity for tigers. Validation of identified corridors through empirical research and their conservation is a priority.

IntroductionConservation research plays an integral role in the effort to conserve biodiversity globally. However, research gaps can limit conservation research’s potential contribution to addressing global biodiversity problems such as habitat fragmentation. While a synthesis of the research literature does not attain effective conservation action by itself, it can inform future research and corridor conservation planning and practices.MethodsWe used a systematic search of peer-reviewed research articles in Scopus, Web of Science, and grey literature in the Connectivity Conservation Specialist Group library published before December 2020. Our review assessed research on the identification and use of corridors, a primary instrument used to address the threats of habitat fragmentation, for large carnivores to identify patterns, priorities, and gaps in the literature. We focused on large carnivores because they are frequently used for connectivity planning owing to their higher sensitivity to habitat fragmentation and their importance as conservation flagship species.Results and discussionWe found that peer-reviewed studies primarily focused on single-species corridors with a strong preference toward apex predators, whereas grey literature focused on multi-species corridors. More than 80% of studies included one of the following five species, the mountain lion (n=46 studies), American black bear (n=31 studies), jaguar (n=25 studies), tiger (n=25 studies), and brown bear (n=18 studies). Although research on the identification of corridors was relatively more common in the past, we found an increasing trend in the publication of studies assessing the use of corridors by large carnivores in recent years. The published research is predominantly from North America (47%) and Asia (30%), with comparatively fewer studies from Africa (4%), despite having several large carnivore species. While climate change and human-wildlife conflict are considered major concerns for large carnivore conservation, these were seldomly considered in corridor research. Corridor research collaborations exist between academia, government, and non-government institutions, but the involvement of the private sector is lacking.ConclusionsOur review shows that there is scope for future corridor research to (i) focus on areas where geographical gaps exist, (ii) target multi-species corridors, (iii) include climate change and human-wildlife conflict scenarios, and iv) increase collaboration with the private sector to better inform connectivity solutions.

This research presents a new model based on Twitter posts and VADER algorithms to analyze social media discourse during and following a bushfire event. The case study is the Gold Coast community that experienced the first bushfire event of Australia’s severe Black Summer in 2019/2020. This study aims to understand which communities and stakeholders generate and exchange information on disasters caused by natural hazards. In doing so, a new methodology to analyze social media in disaster management is presented. This model enables stakeholders to understand key message themes and community sentiment during and following the disaster, as well as the individuals and groups that shape the messaging. Three main findings emerged. Firstly, the results show that messaging volume is a proxy for the importance of the bushfires, with a clear increase during the bushfire event and a sharp decline after the event. Secondly, from a content perspective, there was a consistent negative message sentiment (even during recovery) and the need for better planning, while the links between bushfires and climate change were key message themes. Finally, it was found that politicians, broadcast media and public commentators were central influencers of social media messaging, rather than bushfire experts. This demonstrates the potential of social media to inform disaster response and recovery behavior related to natural hazards.

Abstract Background The skin is both a target and a potential conduit for the delivery of drugs, but its cornified cell layer resists penetration by most molecules. This study investigated the potential of superparamagnetic iron oxide nanoparticles to facilitate the transdermal delivery of anticancer agents. Results Chemotherapeutic cancer drugs were applied with or without nanoparticles to the skin of hairless mice, and their ability to penetrate the skin was assessed using fluorescence microscopy and tumor growth. Nanoparticles enhanced the penetration of the skin by doxorubicin and 5-fluorouracil as determined by fluorescence microscopy and growth retardation of experimental melanoma in immunocompetent, syngeneic mice. This drug enhancement did not require conjugation or encapsulation of the drugs by the nanoparticles—simple co-administration sufficed. Nanoparticles applied topically to melanomas increased the cytotoxicity and immune cell infiltration induced by co-administered 5-fluorouracil, and also reduced vascularization of the tumors independently of 5-fluorouracil. Conclusion Correctly formulated superparamagnetic iron oxide nanoparticles can facilitate the chemotherapeutic effectiveness of cytotoxic drugs on skin tumors by both increasing their transdermal penetration and ameliorating host–tumor interactions. This enhancement of skin penetration occurs without the need for conjugation or encapsulation of the co-administered drugs, and so will likely be applicable to other drugs, also.

The Dark Energy Spectroscopic Instrument, consisting of 5020 robotic fiber positioners and associated systems on the Mayall telescope at Kitt Peak, Arizona, is carrying out a survey to measure the spectra of 40 million galaxies and quasars and produce the largest 3D map of the universe to date. The primary science goal is to use baryon acoustic oscillations to measure the expansion history of the universe and the time evolution of dark energy. A key function of the online control system is to position each fiber on a particular target in the focal plane with an accuracy of 11 μ m rms 2D. This paper describes the set of software programs used to perform this function along with the methods used to validate their performance.

Millions of quasar spectra will be collected by the Dark Energy Spectroscopic Instrument (DESI), leading to a fourfold increase in the number of known quasars. High-accuracy quasar classification is essential to tighten constraints on cosmological parameters measured at the highest redshifts DESI observes ( z > 2.0). We present spectral templates for identification and redshift estimation of quasars in the DESI Year 1 data release. The quasar templates are comprised of two quasar eigenspectra sets, trained on spectra from the Sloan Digital Sky Survey. The sets are specialized to reconstruct quasar spectral variation observed over separate yet overlapping redshift ranges and, together, are capable of identifying DESI quasars from 0.05 < z < 7.0. The new quasar templates show significant improvement over the previous DESI quasar templates regarding catastrophic failure rates, redshift precision and accuracy, quasar completeness, and the contamination fraction in the final quasar sample.

The Dark Energy Spectroscopic Instrument (DESI) Survey has obtained a set of spectroscopic measurements of galaxies to validate the final survey design and target selections. To assist in these tasks, we visually inspect DESI spectra of approximately 2500 bright galaxies, 3500 luminous red galaxies (LRGs), and 10,000 emission-line galaxies (ELGs) to obtain robust redshift identifications. We then utilize the visually inspected redshift information to characterize the performance of the DESI operation. Based on the visual inspection (VI) catalogs, our results show that the final survey design yields samples of bright galaxies, LRGs, and ELGs with purity greater than 99%. Moreover, we demonstrate that the precision of the redshift measurements is approximately 10 km s ^−1 for bright galaxies and ELGs and approximately 40 km s ^−1 for LRGs. The average redshift accuracy is within 10 km s ^−1 for the three types of galaxies. The VI process also helps improve the quality of the DESI data by identifying spurious spectral features introduced by the pipeline. Finally, we show examples of unexpected real astronomical objects, such as Ly α emitters and strong lensing candidates, identified by VI. These results demonstrate the importance and utility of visually inspecting data from incoming and upcoming surveys, especially during their early operation phases.

We present Dark Energy Spectroscopic Instrument (DESI) observations of the inner halo of M31, which reveal the kinematics of a recent merger—a galactic immigration event—in exquisite detail. Of the 11,416 sources studied in 3.75 hr of on-sky exposure time, 7438 are M31 sources with well-measured radial velocities. The observations reveal intricate coherent kinematic structure in the positions and velocities of individual stars: streams, wedges, and chevrons. While hints of coherent structures have been previously detected in M31, this is the first time they have been seen with such detail and clarity in a galaxy beyond the Milky Way. We find clear kinematic evidence for shell structures in the Giant Stellar Stream, the Northeast Shelf, and Western Shelf regions. The kinematics are remarkably similar to the predictions of dynamical models constructed to explain the spatial morphology of the inner halo. The results are consistent with the interpretation that much of the substructure in the inner halo of M31 is produced by a single galactic immigration event 1–2 Gyr ago. Significant numbers of metal-rich stars ([Fe/H] > − 0.5) are present in all of the detected substructures, suggesting that the immigrating galaxy had an extended star formation history. We also investigate the ability of the shells and Giant Stellar Stream to constrain the gravitational potential of M31, and estimate the mass within a projected radius of 125 kpc to be ${\mathrm{log}}_{10}\,{M}_{\mathrm{NFW}}(\lt 125\,\mathrm{kpc})/{M}_{\odot }={11.80}_{-0.10}^{+0.12}$ . The results herald a new era in our ability to study stars on a galactic scale and the immigration histories of galaxies.

The Dark Energy Spectroscopic Instrument (DESI) is carrying out a five-year survey that aims to measure the redshifts of tens of millions of galaxies and quasars, including 8 million luminous red galaxies (LRGs) in the redshift range 0.4 < z ≲ 1.0. Here we present the selection of the DESI LRG sample and assess its spectroscopic performance using data from Survey Validation (SV) and the first two months of the Main Survey. The DESI LRG sample, selected using g , r , z , and W 1 photometry from the DESI Legacy Imaging Surveys, is highly robust against imaging systematics. The sample has a target density of 605 deg ^−2 and a comoving number density of 5 × 10 ^−4 h ^3 Mpc ^−3 in 0.4 < z < 0.8; this is a significantly higher density than previous LRG surveys (such as SDSS, BOSS, and eBOSS) while also extending to z ∼ 1. After applying a bright star veto mask developed for the sample, 98.9% of the observed LRG targets yield confident redshifts (with a catastrophic failure rate of 0.2% in the confident redshifts), and only 0.5% of the LRG targets are stellar contamination. The LRG redshift efficiency varies with source brightness and effective exposure time, and we present a simple model that accurately characterizes this dependence. In the appendices, we describe the extended LRG samples observed during SV.

A key component of the Dark Energy Spectroscopic Instrument (DESI) survey validation (SV) is a detailed visual inspection (VI) of the optical spectroscopic data to quantify key survey metrics. In this paper we present results from VI of the quasar survey using deep coadded SV spectra. We show that the majority (≈70%) of the main-survey targets are spectroscopically confirmed as quasars, with ≈16% galaxies, ≈6% stars, and ≈8% low-quality spectra lacking reliable features. A nonnegligible fraction of the quasars are misidentified by the standard spectroscopic pipeline, but we show that the majority can be recovered using post-pipeline “afterburner” quasar-identification approaches. We combine these “afterburners” with our standard pipeline to create a modified pipeline to increase the overall quasar yield. At the depth of the main DESI survey, both pipelines achieve a good-redshift purity (reliable redshifts measured within 3000 km s ^−1 ) of ≈99%; however, the modified pipeline recovers ≈94% of the visually inspected quasars, as compared to ≈86% from the standard pipeline. We demonstrate that both pipelines achieve a median redshift precision and accuracy of ≈100 km s ^−1 and ≈70 km s ^−1 , respectively. We constructed composite spectra to investigate why some quasars are missed by the standard pipeline and find that they are more host-galaxy dominated (i.e., distant analogs of “Seyfert galaxies”) and/or more dust reddened than the standard-pipeline quasars. We also show example spectra to demonstrate the overall diversity of the DESI quasar sample and provide strong-lensing candidates where two targets contribute to a single spectrum.

The Dark Energy Spectroscopic Instrument (DESI) will precisely constrain cosmic expansion and the growth of structure by collecting ∼40 million extragalactic redshifts across ∼80% of cosmic history and one-third of the sky. The Emission Line galaxy (ELG) sample, which will comprise about one-third of all DESI tracers, will be used to probe the universe over the 0.6 < z < 1.6 range, including the 1.1 < z < 1.6 range, which is expected to provide the tightest constraints. We present the target selection for the DESI Survey Validation (SV) and Main Survey ELG samples, which relies on the imaging of the Legacy Surveys. The Main ELG selection consists of a g -band magnitude cut and a ( g − r ) versus ( r − z ) color box, while the SV selection explores extensions of the Main selection boundaries. The Main ELG sample is composed of two disjoint subsamples, which have target densities of about 1940 deg ^−2 and 460 deg ^−2 , respectively. We first characterize their photometric properties and density variations across the footprint. We then analyze the DESI spectroscopic data that have been obtained from 2020 December to 2021 December in the SV and Main Survey. We establish a preliminary criterion for selecting reliable redshifts, based on the [O ii ] flux measurement, and assess its performance. Using this criterion, we are able to present the spectroscopic efficiency of the Main ELG selection, along with its redshift distribution. We thus demonstrate that the Main selection 1940 deg ^−2 subsample alone should provide 400 deg ^−2 and 460 deg ^−2 reliable redshifts in the 0.6 < z < 1.1 and the 1.1 < z < 1.6 ranges, respectively.

We describe the spectroscopic data processing pipeline of the Dark Energy Spectroscopic Instrument (DESI), which is conducting a redshift survey of about 40 million galaxies and quasars using a purpose-built instrument on the 4 m Mayall Telescope at Kitt Peak National Observatory. The main goal of DESI is to measure with unprecedented precision the expansion history of the universe with the baryon acoustic oscillation technique and the growth rate of structure with redshift space distortions. Ten spectrographs with three cameras each disperse the light from 5000 fibers onto 30 CCDs, covering the near-UV to near-infrared (3600–9800 Å) with a spectral resolution ranging from 2000 to 5000. The DESI data pipeline generates wavelength- and flux-calibrated spectra of all the targets, along with spectroscopic classifications and redshift measurements. Fully processed data from each night are typically available to the DESI collaboration the following morning. We give details about the pipeline’s algorithms, and provide performance results on the stability of the optics, the quality of the sky background subtraction, and the precision and accuracy of the instrumental calibration. This pipeline has been used to process the DESI Survey Validation data set, and has exceeded the project’s requirements for redshift performance, with high efficiency and a purity greater than 99% for all target classes.

Tobacco use is one of the major risk factors for Head and neck squamous cell carcinoma (HNSCC). Here, the authors report an immune-competent syngeneic mouse model that mimics human tobacco-related HNSCC, and develops tumors in the tongue, and report a high response rate to anti-CTLA-4 therapy.

Summary: It is thought that corneal epithelial injuries resolve by leading-edge cells “sliding” or “rolling” into the wound bed. Here, we challenge this notion and show by real-time imaging that corneal wounds initially heal by “basal cell migration.” The K14CreERT2-Confetti multi-colored reporter mouse was employed to spatially and temporally fate-map cellular behavior during corneal wound healing. Keratin-14+ basal epithelia are forced into the wound bed by increased population pressure gradient from the limbus to the wound edge. As the defect resolves, centripetally migrating epithelia decelerate and replication in the periphery is reduced. With time, keratin-14+-derived clones diminish in number concomitant with their expansion, indicative that clonal evolution aligns with neutral drifting. These findings have important implications for the involvement of stem cells in acute tissue regeneration, in key sensory tissues such as the cornea. : In this article, Di Girolamo and colleagues visualized the contribution of K14+ limbal epithelial precursors in resolving corneal epithelial debridement wounds. They noted that population pressure from the limbal perimeter is the main driver of K14+ basal cell displacement during the initial phase of injury repair. Keywords: cornea wound healing, limbal epithelial stem cells, K14CreERT2-Confetti transgenic mice, basal cell migration, organ-culture system, spatiotemporal image correlation spectroscopy, computational modeling

Summary: To better understand the influence of ultraviolet (UV) irradiation on the initial steps of skin carcinogenesis, we examine patches of labeled keratinocytes as a proxy for clones in the interfollicular epidermis (IFE) and measure their size variation upon UVB irradiation. Multicolor lineage tracing reveals that in chronically irradiated skin, patches near hair follicles (HFs) increase in size, whereas those far from follicles do not change. This is explained by proliferation of basal epidermal cells within 60 μm of HF openings. Upon interruption of UVB, patch size near HFs regresses significantly. These anatomical differences in proliferative behavior have significant consequences for the cell of origin of basal cell carcinomas (BCCs). Indeed, a UV-inducible murine BCC model shows that BCC patches are more frequent, larger, and more invasive near HFs. These findings have major implications for the prevention of field cancerization in the epidermis.

The Dark Energy Spectroscopic Instrument (DESI) embarked on an ambitious 5 yr survey in 2021 May to explore the nature of dark energy with spectroscopic measurements of 40 million galaxies and quasars. DESI will determine precise redshifts and employ the baryon acoustic oscillation method to measure distances from the nearby universe to beyond redshift z > 3.5, and employ redshift space distortions to measure the growth of structure and probe potential modifications to general relativity. We describe the significant instrumentation we developed to conduct the DESI survey. This includes: a wide-field, 3.°2 diameter prime-focus corrector; a focal plane system with 5020 fiber positioners on the 0.812 m diameter, aspheric focal surface; 10 continuous, high-efficiency fiber cable bundles that connect the focal plane to the spectrographs; and 10 identical spectrographs. Each spectrograph employs a pair of dichroics to split the light into three channels that together record the light from 360–980 nm with a spectral resolution that ranges from 2000–5000. We describe the science requirements, their connection to the technical requirements, the management of the project, and interfaces between subsystems. DESI was installed at the 4 m Mayall Telescope at Kitt Peak National Observatory and has achieved all of its performance goals. Some performance highlights include an rms positioner accuracy of better than 0.″1 and a median signal-to-noise ratio of 7 of the [O ii ] doublet at 8 × 10 ^−17 erg s ^−1 cm ^−2 in 1000 s for galaxies at z = 1.4–1.6. We conclude with additional highlights from the on-sky validation and commissioning, key successes, and lessons learned.

Dysregulation of the Hippo signaling is a frequent event in human malignancies, but the molecular mechanisms remain unclear. Here the authors show that in head and neck squamous carcinoma, FAT1 interacts with the Hippo signaling complex, resulting in the activation of core Hippo kinases and YAP1 inactivation.

The dynamics of epithelial stem cells (SCs) that contribute to the formation and maintenance of the cornea are poorly understood. Here, we used K14CreERT2-Confetti (Confetti) mice, sophisticated imaging, and computational modeling to trace the origins and fate of these cells during embryogenesis and adult life. We show that keratin-14 (K14+)-expressing progenitors are defined and widely distributed across the E16.5 cornea, after which they undergo cycles of proliferation and dispersal prior to eyelid opening. K14+ clonal patches disappear from the central cornea and are replaced by limbal-derived K14+ streaks, a finding that aligned with bromodeoxyuridine label-retaining studies. We also elucidated the mechanism by which SC clones are lost during life and propose this is due to population asymmetry and neutral drift. Finally, we established that the occurrence of an equatorial migratory mid-line is a consequence of apoptosis in a narrow nasal-temporal region, the site where eyelids meet during blinking.

Martinotti cells disinhibit excitatory cells in the brain cortex and play an important role in information flow. Here the authors study the role of parvalbumin and vasoactive intestinal polypeptide interneurons on the inhibition of Martinotti cells in the mouse somatosensory cortex.

The meibomian and sebaceous glands secrete lipids to prevent desiccation of the ocular surface and skin, respectively. Precisely how these holocrine tissues regenerate is not well understood. To address this, we characterized keratin 5+ (K5) label-retaining cells (LRCs) and the lineage tracing of keratin 14 (K14) progenitors in mouse meibomian glands. Using the tet-off H2B-GFP/K5tTA mouse, H2B-GFP fluorescence dilutes 2-fold with every division in K5+ cell nuclei after doxycycline administration. In 3D reconstructions generated over a >28-day doxycycline chase, we observed LRCs at the acinus entrance where K6+ ductal epithelium terminates. For lineage tracing, K14CreERT2-Confetti mice were injected intraperitoneally with tamoxifen and euthanized at 23 and 59 weeks later. Meibomian gland acini in these mice were either monochromatic or dual-colored, whereas the duct exhibited multiple colors. In conclusion, LRCs are likely to direct meibomian gland turnover and may exist as two distinct unipotent progenitors that renew ductal and acinar tissue separately.

The cornea is formed of cells that originate from the outer circle of stem cells and that move towards its centre. Here, the authors show that the movement pattern is self-organised, requiring no cues, and that stem cell leakage may account for the presence of stem cells at the centre of the cornea.

The fungal skin disease, chytridiomycosis (caused by Batrachochytrium dendrobatidis and B. salamandrivorans), has caused amphibian declines and extinctions globally since its emergence. Characterizing the host immune response to chytridiomycosis has been a focus of study with the aim of disease mitigation. However, many aspects of the innate and adaptive arms of this response are still poorly understood, likely due to the wide range of species' responses to infection. In this paper we provide an overview of expected immunological responses (with inference based on amphibian and mammalian immunology), together with a synthesis of current knowledge about these responses for the amphibian-chytridiomycosis system. We structure our review around four key immune stages: (1) the naïve immunocompetent state, (2) immune defenses that are always present (constitutive defenses), (3) mechanisms for recognition of a pathogen threat and innate immune defenses, and (4) adaptive immune responses. We also evaluate the current hot topics of immunosuppression and immunopathology in chytridiomycosis, and discuss their respective roles in pathogenesis. Our synthesis reveals that susceptibility to chytridiomycosis is likely to be multifactorial. Susceptible amphibians appear to have ineffective constitutive and innate defenses, and a late-stage response characterized by immunopathology and Bd-induced suppression of lymphocyte responses. Overall, we identify substantial gaps in current knowledge, particularly concerning the entire innate immune response (mechanisms of initial pathogen detection and possible immunoevasion by Bd, degree of activation and efficacy of the innate immune response, the unexpected absence of innate leukocyte infiltration, and the cause and role of late-stage immunopathology in pathogenesis). There are also gaps concerning most of the adaptive immune system (the relative importance of B and T cell responses for pathogen clearance, the capacity and extent of immunological memory, and specific mechanisms of pathogen-induced immunosuppression). Improving our capacity for amphibian immunological research will require selection of an appropriate Bd-susceptible model species, the development of taxon-specific affinity reagents and cell lines for functional assays, and the application of a suite of conventional and emerging immunological methods. Despite current knowledge gaps, immunological research remains a promising avenue for amphibian conservation management.

The hadronic part of the electron structure function F2e has been measured for the first time, using e+e− data collected by the DELPHI experiment at LEP, at centre-of-mass energies of s=91.2–209.5 GeV. The data analysis is simpler than that of the measurement of the photon structure function. The electron structure function F2e data are compared to predictions of phenomenological models based on the photon structure function. It is shown that the contribution of large target photon virtualities is significant. The data presented can serve as a cross-check of the photon structure function F2γ analyses and help in refining existing parameterisations.

During COVID-19 lockdowns, online learning activities had to be developed for the Undergraduate and Masters by Coursework Bioinformatics students at RMIT University. Therefore, we designed an integrative, industry-based research assignment, which guided the students through a drug discovery project from target identification to lead optimization. The students were able to utilize this real-life scenario to apply multiple diverse but complementary bioinformatic principles to analyze biological and chemical data leading to meaningful predictions. This activity was utilized as a final assessment of the students' knowledge.

The nitric oxide synthase-like protein from Bacillus cereus (bcNOS) has been cloned, expressed, and characterized. This small hemeprotein (356 amino acids in length) has a mass of 43 kDa and forms a dimer. The recombinant protein showed similar spectral shifts to the mammalian NOS proteins and could bind the substrates L-arginine and NG-hydroxy-L-arginine as well as the ligand imidazole. Low levels of activity were recorded for the hydrogen peroxide-dependent oxidation of NG-hydroxy-L-arginine and L-arginine by bcNOS, while a reconstituted system with the rat neuronal NOS reductase domain showed no activity. The recombinant bcNOS protein adds to the complement of bacterial NOS-like proteins that are used for the investigation of the mechanism and function of NO in microorganisms.

Head and neck squamous cell carcinoma (HNSCC) is the sixth most common cancer worldwide. Tobacco use is the main risk factor for HNSCC, and tobacco-associated HNSCCs have poor prognosis and response to available treatments. Recently approved anti-PD-1 immune checkpoint inhibitors showed limited activity (≤20%) in HNSCC, highlighting the need to identify new therapeutic options. For this, mouse models that accurately mimic the complexity of the HNSCC mutational landscape and tumor immune environment are urgently needed. Here, we report a mouse HNSCC model system that recapitulates the human tobacco-related HNSCC mutanome, in which tumors grow when implanted in the tongue of immunocompetent mice. These HNSCC lesions have similar immune infiltration and response rates to anti-PD-1 (≤20%) immunotherapy as human HNSCCs. Remarkably, we find that >70% of HNSCC lesions respond to intratumoral anti-CTLA-4. This syngeneic HNSCC mouse model provides a platform to accelerate the development of immunotherapeutic options for HNSCC.