New reptile shows dinosaurs and pterosaurs evolved among diverse precursors.

Dinosaurs and pterosaurs have remarkable diversity and disparity through most of the Mesozoic Era1-3. Soon after their origins, these reptiles diversified into a number of long-lived lineages, evolved unprecedented ecologies (for example, flying, large herbivorous forms) and spread across Pangaea4,5. Recent discoveries of dinosaur and pterosaur precursors6-10 demonstrated that these animals were also speciose and widespread, but those precursors have few if any well-preserved skulls, hands and associated skeletons11,12. Here we present a well-preserved partial skeleton (Upper Triassic, Brazil) of the new lagerpetid Venetoraptor gassenae gen. et sp. nov. that offers a more comprehensive look into the skull and ecology of one of these precursors. Its skull has a sharp, raptorial-like beak, preceding that of dinosaurs by around 80 million years, and a large hand with long, trenchant claws that firmly establishes the loss of obligatory quadrupedalism in these precursor lineages. Combining anatomical information of the new species with other dinosaur and pterosaur precursors shows that morphological disparity of precursors resembles that of Triassic pterosaurs and exceeds that of Triassic dinosaurs. Thus, the 'success' of pterosaurs and dinosaurs was a result of differential survival among a broader pool of ecomorphological variation. Our results show that the morphological diversity of ornithodirans started to flourish among early-diverging lineages and not only after the origins of dinosaurs and pterosaurs.

Enigmatic dinosaur precursors bridge the gap to the origin of Pterosauria.

Pterosaurs were the first vertebrates to evolve powered flight1 and comprised one of the main evolutionary radiations in terrestrial ecosystems of the Mesozoic era (approximately 252-66 million years ago), but their origin has remained an unresolved enigma in palaeontology since the nineteenth century2-4. These flying reptiles have been hypothesized to be the close relatives of a wide variety of reptilian clades, including dinosaur relatives2-8, and there is still a major morphological gap between those forms and the oldest, unambiguous pterosaurs from the Upper Triassic series. Here, using recent discoveries of well-preserved cranial remains, microcomputed tomography scans of fragile skull bones (jaws, skull roofs and braincases) and reliably associated postcrania, we demonstrate that lagerpetids-a group of cursorial, non-volant dinosaur precursors-are the sister group of pterosaurs, sharing numerous synapomorphies across the entire skeleton. This finding substantially shortens the temporal and morphological gap between the oldest pterosaurs and their closest relatives and simultaneously strengthens the evidence that pterosaurs belong to the avian line of archosaurs. Neuroanatomical features related to the enhanced sensory abilities of pterosaurs9 are already present in lagerpetids, which indicates that these features evolved before flight. Our evidence illuminates the first steps of the assembly of the pterosaur body plan, whose conquest of aerial space represents a remarkable morphofunctional innovation in vertebrate evolution.

Human brain effects of DMT assessed via EEG-fMRI.

Psychedelics have attracted medical interest, but their effects on human brain function are incompletely understood. In a comprehensive, within-subjects, placebo-controlled design, we acquired multimodal neuroimaging [i.e., EEG-fMRI (electroencephalography-functional MRI)] data to assess the effects of intravenous (IV) N,N-Dimethyltryptamine (DMT) on brain function in 20 healthy volunteers. Simultaneous EEG-fMRI was acquired prior to, during, and after a bolus IV administration of 20 mg DMT, and, separately, placebo. At dosages consistent with the present study, DMT, a serotonin 2A receptor (5-HT2AR) agonist, induces a deeply immersive and radically altered state of consciousness. DMT is thus a useful research tool for probing the neural correlates of conscious experience. Here, fMRI results revealed robust increases in global functional connectivity (GFC), network disintegration and desegregation, and a compression of the principal cortical gradient under DMT. GFC × subjective intensity maps correlated with independent positron emission tomography (PET)-derived 5-HT2AR maps, and both overlapped with meta-analytical data implying human-specific psychological functions. Changes in major EEG-measured neurophysiological properties correlated with specific changes in various fMRI metrics, enriching our understanding of the neural basis of DMT's effects. The present findings advance on previous work by confirming a predominant action of DMT-and likely other 5-HT2AR agonist psychedelics-on the brain's transmodal association pole, i.e., the neurodevelopmentally and evolutionarily recent cortex that is associated with species-specific psychological advancements, and high expression of 5-HT2A receptors.

Synergistic information supports modality integration and flexible learning in neural networks solving multiple tasks.

Striking progress has been made in understanding cognition by analyzing how the brain is engaged in different modes of information processing. For instance, so-called synergistic information (information encoded by a set of neurons but not by any subset) plays a key role in areas of the human brain linked with complex cognition. However, two questions remain unanswered: (a) how and why a cognitive system can become highly synergistic; and (b) how informational states map onto artificial neural networks in various learning modes. Here we employ an information-decomposition framework to investigate neural networks performing cognitive tasks. Our results show that synergy increases as networks learn multiple diverse tasks, and that in tasks requiring integration of multiple sources, performance critically relies on synergistic neurons. Overall, our results suggest that synergy is used to combine information from multiple modalities-and more generally for flexible and efficient learning. These findings reveal new ways of investigating how and why learning systems employ specific information-processing strategies, and support the principle that the capacity for general-purpose learning critically relies on the system's information dynamics.

A role for the serotonin 2A receptor in the expansion and functioning of human transmodal cortex.

Integrating independent but converging lines of research on brain function and neurodevelopment across scales, this article proposes that serotonin 2A receptor (5-HT2AR) signalling is an evolutionary and developmental driver and potent modulator of the macroscale functional organization of the human cerebral cortex. A wealth of evidence indicates that the anatomical and functional organization of the cortex follows a unimodal-to-transmodal gradient. Situated at the apex of this processing hierarchy-where it plays a central role in the integrative processes underpinning complex, human-defining cognition-the transmodal cortex has disproportionately expanded across human development and evolution. Notably, the adult human transmodal cortex is especially rich in 5-HT2AR expression and recent evidence suggests that, during early brain development, 5-HT2AR signalling on neural progenitor cells stimulates their proliferation-a critical process for evolutionarily-relevant cortical expansion. Drawing on multimodal neuroimaging and cross-species investigations, we argue that, by contributing to the expansion of the human cortex and being prevalent at the apex of its hierarchy in the adult brain, 5-HT2AR signalling plays a major role in both human cortical expansion and functioning. Owing to its unique excitatory and downstream cellular effects, neuronal 5-HT2AR agonism promotes neuroplasticity, learning and cognitive and psychological flexibility in a context-(hyper)sensitive manner with therapeutic potential. Overall, we delineate a dual role of 5-HT2ARs in enabling both the expansion and modulation of the human transmodal cortex.

MobiDB: 10 years of intrinsically disordered proteins.

The MobiDB database (URL: https://mobidb.org/) is a knowledge base of intrinsically disordered proteins. MobiDB aggregates disorder annotations derived from the literature and from experimental evidence along with predictions for all known protein sequences. MobiDB generates new knowledge and captures the functional significance of disordered regions by processing and combining complementary sources of information. Since its first release 10 years ago, the MobiDB database has evolved in order to improve the quality and coverage of protein disorder annotations and its accessibility. MobiDB has now reached its maturity in terms of data standardization and visualization. Here, we present a new release which focuses on the optimization of user experience and database content. The major advances compared to the previous version are the integration of AlphaFoldDB predictions and the re-implementation of the homology transfer pipeline, which expands manually curated annotations by two orders of magnitude. Finally, the entry page has been restyled in order to provide an overview of the available annotations along with two separate views that highlight structural disorder evidence and functions associated with different binding modes.

Sodium nitroprusside enhances stepping test performance and increases medium spiny neurons responsiveness to cortical inputs in a rat model of Levodopa-induced dyskinesias.

Levodopa (L-DOPA) is the classical gold standard treatment for Parkinson's disease. However, its chronic administration can lead to the development of L-DOPA-induced dyskinesias (LIDs). Dysregulation of the nitric oxide-cyclic guanosine monophosphate pathway in striatal networks has been linked to deficits in corticostriatal transmission in LIDs. This study investigated the effects of the nitric oxide (NO) donor sodium nitroprusside (SNP) on behavioural and electrophysiological outcomes in sham-operated and 6-hydroxydopamine-lesioned rats chronically treated with vehicle or L-DOPA, respectively. In sham-operated animals, systemic administration of SNP increased the spike probability of putative striatal medium spiny neurons (MSNs) in response to electrical stimulation of the primary motor cortex. In 6-hydroxydopamine-lesioned animals, SNP improved the stepping test performance without exacerbating abnormal involuntary movements. Additionally, SNP significantly increased the responsiveness of putative striatal MSNs in the dyskinetic striatum. These findings highlight the critical role of the NO signalling pathway in facilitating the responsiveness of striatal MSNs in both the intact and dyskinetic striata. The study suggests that SNP has the potential to enhance L-DOPA's effects in the stepping test without exacerbating abnormal involuntary movements, thereby offering new possibilities for optimizing Parkinson's disease therapy. In conclusion, this study highlights the involvement of the NO signalling pathway in the pathophysiology of LIDs.

Improved reconstruction of crossing fibers in the mouse optic pathways with orientation distribution function fingerprinting.

PURPOSE: The accuracy of diffusion MRI tractography reconstruction decreases in the white matter regions with crossing fibers. The optic pathways in rodents provide a challenging structure to test new diffusion tractography approaches because of the small crossing volume within the optic chiasm and the unbalanced 9:1 proportion between the contra- and ipsilateral neural projections from the retina to the lateral geniculate nucleus, respectively. METHODS: Common approaches based on Orientation Distribution Function (ODF) peak finding or statistical inference were compared qualitatively and quantitatively to ODF Fingerprinting (ODF-FP) for reconstruction of crossing fibers within the optic chiasm using in vivo diffusion MRI ( n = 18 $$ n=18 $$ healthy C57BL/6 mice). Manganese-Enhanced MRI (MEMRI) was obtained after intravitreal injection of manganese chloride and used as a reference standard for the optic pathway anatomy. RESULTS: ODF-FP outperformed by over 100% all the tested methods in terms of the ratios between the contra- and ipsilateral segments of the reconstructed optic pathways as well as the spatial overlap between tractography and MEMRI. CONCLUSION: In this challenging model system, ODF-Fingerprinting reduced uncertainty of diffusion tractography for complex structural formations of fiber bundles.

Assessing expectancy and suggestibility in a trial of escitalopram v. psilocybin for depression.

BACKGROUND: To investigate the association between pre-trial expectancy, suggestibility, and response to treatment in a trial of escitalopram and investigational drug, COMP360, psilocybin, in the treatment of major depressive disorder (ClinicalTrials.gov registration: NCT03429075). METHODS: We used data (n = 55) from our recent double-blind, parallel-group, randomized head-to-head comparison trial of escitalopram and investigational drug, COMP360, psilocybin. Mixed linear models were used to investigate the association between pre-treatment efficacy-related expectations, as well as baseline trait suggestibility and absorption, and therapeutic response to both escitalopram and COMP360 psilocybin. RESULTS: Patients had significantly higher expectancy for psilocybin relative to escitalopram; however, expectancy for escitalopram was associated with improved therapeutic outcomes to escitalopram, expectancy for psilocybin was not predictive of response to psilocybin. Separately, we found that pre-treatment trait suggestibility was associated with therapeutic response in the psilocybin arm, but not in the escitalopram arm. CONCLUSIONS: Overall, our results suggest that psychedelic therapy may be less vulnerable to expectancy biases than previously suspected. The relationship between baseline trait suggestibility and response to psilocybin therapy implies that highly suggestible individuals may be primed for response to this treatment.

LSD-induced increase of Ising temperature and algorithmic complexity of brain dynamics.

A topic of growing interest in computational neuroscience is the discovery of fundamental principles underlying global dynamics and the self-organization of the brain. In particular, the notion that the brain operates near criticality has gained considerable support, and recent work has shown that the dynamics of different brain states may be modeled by pairwise maximum entropy Ising models at various distances from a phase transition, i.e., from criticality. Here we aim to characterize two brain states (psychedelics-induced and placebo) as captured by functional magnetic resonance imaging (fMRI), with features derived from the Ising spin model formalism (system temperature, critical point, susceptibility) and from algorithmic complexity. We hypothesized, along the lines of the entropic brain hypothesis, that psychedelics drive brain dynamics into a more disordered state at a higher Ising temperature and increased complexity. We analyze resting state blood-oxygen-level-dependent (BOLD) fMRI data collected in an earlier study from fifteen subjects in a control condition (placebo) and during ingestion of lysergic acid diethylamide (LSD). Working with the automated anatomical labeling (AAL) brain parcellation, we first create "archetype" Ising models representative of the entire dataset (global) and of the data in each condition. Remarkably, we find that such archetypes exhibit a strong correlation with an average structural connectome template obtained from dMRI (r = 0.6). We compare the archetypes from the two conditions and find that the Ising connectivity in the LSD condition is lower than in the placebo one, especially in homotopic links (interhemispheric connectivity), reflecting a significant decrease of homotopic functional connectivity in the LSD condition. The global archetype is then personalized for each individual and condition by adjusting the system temperature. The resulting temperatures are all near but above the critical point of the model in the paramagnetic (disordered) phase. The individualized Ising temperatures are higher in the LSD condition than in the placebo condition (p = 9 × 10-5). Next, we estimate the Lempel-Ziv-Welch (LZW) complexity of the binarized BOLD data and the synthetic data generated with the individualized model using the Metropolis algorithm for each participant and condition. The LZW complexity computed from experimental data reveals a weak statistical relationship with condition (p = 0.04 one-tailed Wilcoxon test) and none with Ising temperature (r(13) = 0.13, p = 0.65), presumably because of the limited length of the BOLD time series. Similarly, we explore complexity using the block decomposition method (BDM), a more advanced method for estimating algorithmic complexity. The BDM complexity of the experimental data displays a significant correlation with Ising temperature (r(13) = 0.56, p = 0.03) and a weak but significant correlation with condition (p = 0.04, one-tailed Wilcoxon test). This study suggests that the effects of LSD increase the complexity of brain dynamics by loosening interhemispheric connectivity-especially homotopic links. In agreement with earlier work using the Ising formalism with BOLD data, we find the brain state in the placebo condition is already above the critical point, with LSD resulting in a shift further away from criticality into a more disordered state.

A new abelisaurid dinosaur from the end Cretaceous of Patagonia and evolutionary rates among the Ceratosauria.

Gondwanan dinosaur faunae during the 20 Myr preceding the Cretaceous-Palaeogene (K/Pg) extinction included several lineages that were absent or poorly represented in Laurasian landmasses. Among these, the South American fossil record contains diverse abelisaurids, arguably the most successful groups of carnivorous dinosaurs from Gondwana in the Cretaceous, reaching their highest diversity towards the end of this period. Here we describe Koleken inakayali gen. et sp. n., a new abelisaurid from the La Colonia Formation (Maastrichtian, Upper Cretaceous) of Patagonia. Koleken inakayali is known from several skull bones, an almost complete dorsal series, complete sacrum, several caudal vertebrae, pelvic girdle and almost complete hind limbs. The new abelisaurid shows a unique set of features in the skull and several anatomical differences from Carnotaurus sastrei (the only other abelisaurid known from the La Colonia Formation). Koleken inakayali is retrieved as a brachyrostran abelisaurid, clustered with other South American abelisaurids from the latest Cretaceous (Campanian-Maastrichtian), such as Aucasaurus, Niebla and Carnotaurus. Leveraging our phylogeny estimates, we explore rates of morphological evolution across ceratosaurian lineages, finding them to be particularly high for elaphrosaurine noasaurids and around the base of Abelisauridae, before the Early Cretaceous radiation of the latter clade. The Noasauridae and their sister clade show contrasting patterns of morphological evolution, with noasaurids undergoing an early phase of accelerated evolution of the axial and hind limb skeleton in the Jurassic, and the abelisaurids exhibiting sustained high rates of cranial evolution during the Early Cretaceous. These results provide much needed context for the evolutionary dynamics of ceratosaurian theropods, contributing to broader understanding of macroevolutionary patterns across dinosaurs.

Actin dynamics regulation by TTC7A/PI4KIIIα limits DNA damage and cell death under confinement.

BACKGROUND: The actin cytoskeleton has a crucial role in the maintenance of the immune homeostasis by controlling various cellular processes, including cell migration. Mutations in TTC7A have been described as the cause of a primary immunodeficiency associated to different degrees of gut involvement and alterations in the actin cytoskeleton dynamics. OBJECTIVES: This study investigates the impact of TTC7A deficiency in immune homeostasis. In particular, the role of the TTC7A/phosphatidylinositol 4 kinase type III α pathway in the control of leukocyte migration and actin dynamics. METHODS: Microfabricated devices were leveraged to study cell migration and actin dynamics of murine and patient-derived leukocytes under confinement at the single-cell level. RESULTS: We show that TTC7A-deficient lymphocytes exhibit an altered cell migration and reduced capacity to deform through narrow gaps. Mechanistically, TTC7A-deficient phenotype resulted from impaired phosphoinositide signaling, leading to the downregulation of the phosphoinositide 3-kinase/AKT/RHOA regulatory axis and imbalanced actin cytoskeleton dynamics. TTC7A-associated phenotype resulted in impaired cell motility, accumulation of DNA damage, and increased cell death in dense 3-dimensional gels in the presence of chemokines. CONCLUSIONS: These results highlight a novel role of TTC7A as a critical regulator of lymphocyte migration. Impairment of this cellular function is likely to contribute to the pathophysiology underlying progressive immunodeficiency in patients.

An information-theoretic approach to build hypergraphs in psychometrics.

Psychological network approaches propose to see symptoms or questionnaire items as interconnected nodes, with links between them reflecting pairwise statistical dependencies evaluated on cross-sectional, time-series, or panel data. These networks constitute an established methodology to visualise and conceptualise the interactions and relative importance of nodes/indicators, providing an important complement to other approaches such as factor analysis. However, limiting the representation to pairwise relationships can neglect potentially critical information shared by groups of three or more variables (higher-order statistical interdependencies). To overcome this important limitation, here we propose an information-theoretic framework to assess these interdependencies and consequently to use hypergraphs as representations in psychometrics. As edges in hypergraphs are capable of encompassing several nodes together, this extension can thus provide a richer account on the interactions that may exist among sets of psychological variables. Our results show how psychometric hypergraphs can highlight meaningful redundant and synergistic interactions on either simulated or state-of-the-art, re-analysed psychometric datasets. Overall, our framework extends current network approaches while leading to new ways of assessing the data that differ at their core from other methods, enriching the psychometrics toolbox, and opening promising avenues for future investigation.

The high identity of the Trypanosoma cruzi Group-I of trans-sialidases points them as promising vaccine immunogens.

Trans-sialidase (TS) superfamily of proteins comprises eight subgroups, being the proteins of Group-I (TS-GI) promising immunogens in vaccine approaches against Trypanosoma cruzi. Strikingly, TS-GI antigenic variability among parasite lineages and their influence on vaccine development has not been previously analyzed. Here, a search in GenBank detects 49 TS-GI indexed sequences, whereas the main infecting human different parasite discrete typing units (DTU) are represented. In silico comparison among these sequences indicate that they share an identity above 92%. Moreover, the antigenic regions (T-cell and B-cell epitopes) are conserved in most sequences or present amino acid substitutions that scarcely may alter the antigenicity. Additionally, since the generic term TS is usually used to refer to different immunogens of this broad family, a further in silico analysis of the TS-GI-derived fragments tested in preclinical vaccines was done to determine the coverage and identity among them, showing that overall amino acid identity of vaccine immunogens is high, but the segment coverage varies widely. Accordingly, strong H-2K, H-2I, and B-cell epitopes are dissimilarly represented among vaccine TS-derived fragments depending on the extension of the TG-GI sequence used. Moreover, bioinformatic analysis detected a set of 150 T-cell strong epitopes among the DTU-indexed sequences that strongly bind human HLA-I supertypes. In all currently reported experimental vaccines based on TS-GI fragments, mapping these 150 epitopes showed that they are moderately represented. However, despite vaccine epitopes do not present all the substitutions observed in the DTUs, these regions of the proteins are equally recognized by the same HLAs.  Interestingly, the predictions regarding global and South American population coverage estimated in these 150 epitopes are similar to the estimations in experimental vaccines when the complete sequence of TS-GI is used as an antigen. In silico prediction also shows that a number of these MHC-I restricted T-cell strong epitopes could be also cross-recognized by HLA-I supertypes and H-2Kb or H-2Kd backgrounds, indicating that these mice may be used to improve and facilitate the development of new TS-based vaccines and suggesting an immunogenic and protective potential in humans. Further molecular docking analyses were performed to strengthen these results. Taken together, different strategies that would cover more or eventually fully of these T-cell and also B-cell epitopes to reach a high level of coverage are considered.

Reduced emergent character of neural dynamics in patients with a disrupted connectome.

High-level brain functions are widely believed to emerge from the orchestrated activity of multiple neural systems. However, lacking a formal definition and practical quantification of emergence for experimental data, neuroscientists have been unable to empirically test this long-standing conjecture. Here we investigate this fundamental question by leveraging a recently proposed framework known as "Integrated Information Decomposition," which establishes a principled information-theoretic approach to operationalise and quantify emergence in dynamical systems - including the human brain. By analysing functional MRI data, our results show that the emergent and hierarchical character of neural dynamics is significantly diminished in chronically unresponsive patients suffering from severe brain injury. At a functional level, we demonstrate that emergence capacity is positively correlated with the extent of hierarchical organisation in brain activity. Furthermore, by combining computational approaches from network control theory and whole-brain biophysical modelling, we show that the reduced capacity for emergent and hierarchical dynamics in severely brain-injured patients can be mechanistically explained by disruptions in the patients' structural connectome. Overall, our results suggest that chronic unresponsiveness resulting from severe brain injury may be related to structural impairment of the fundamental neural infrastructures required for brain dynamics to support emergence.

Computational modelling in disorders of consciousness: Closing the gap towards personalised models for restoring consciousness.

Disorders of consciousness are complex conditions characterised by persistent loss of responsiveness due to brain injury. They present diagnostic challenges and limited options for treatment, and highlight the urgent need for a more thorough understanding of how human consciousness arises from coordinated neural activity. The increasing availability of multimodal neuroimaging data has given rise to a wide range of clinically- and scientifically-motivated modelling efforts, seeking to improve data-driven stratification of patients, to identify causal mechanisms for patient pathophysiology and loss of consciousness more broadly, and to develop simulations as a means of testing in silico potential treatment avenues to restore consciousness. As a dedicated Working Group of clinicians and neuroscientists of the international Curing Coma Campaign, here we provide our framework and vision to understand the diverse statistical and generative computational modelling approaches that are being employed in this fast-growing field. We identify the gaps that exist between the current state-of-the-art in statistical and biophysical computational modelling in human neuroscience, and the aspirational goal of a mature field of modelling disorders of consciousness; which might drive improved treatments and outcomes in the clinic. Finally, we make several recommendations for how the field as a whole can work together to address these challenges.

Tractography passes the test: Results from the diffusion-simulated connectivity (disco) challenge.

Estimating structural connectivity from diffusion-weighted magnetic resonance imaging is a challenging task, partly due to the presence of false-positive connections and the misestimation of connection weights. Building on previous efforts, the MICCAI-CDMRI Diffusion-Simulated Connectivity (DiSCo) challenge was carried out to evaluate state-of-the-art connectivity methods using novel large-scale numerical phantoms. The diffusion signal for the phantoms was obtained from Monte Carlo simulations. The results of the challenge suggest that methods selected by the 14 teams participating in the challenge can provide high correlations between estimated and ground-truth connectivity weights, in complex numerical environments. Additionally, the methods used by the participating teams were able to accurately identify the binary connectivity of the numerical dataset. However, specific false positive and false negative connections were consistently estimated across all methods. Although the challenge dataset doesn't capture the complexity of a real brain, it provided unique data with known macrostructure and microstructure ground-truth properties to facilitate the development of connectivity estimation methods.

Mitigating challenges in aberration-corrected electron-beam lithography on electron-opaque substrates.

Aberration-corrected electron-beam lithography (AC-EBL) using ultra-thin electron transparent membranes has achieved single-digit nanometer resolution in two widely used electron-beam resists: poly (methyl methacrylate) (PMMA) and hydrogen silsesquioxane. On the other hand, AC-EBL implementation on thick, electron-opaque substrates is appealing for conventional top-down fabrication of quantum devices with nanometer-scale features. To investigate the performance of AC-EBL on thick substrates, we measured the lithographic point spread function of a 200 keV aberration-corrected scanning transmission electron microscope by defining both positive and negative patterns in PMMA thin films, spin-cast on thick SiO2/Si substrates. We present the problems encountered during pre-exposure beam focusing and discuss methods to overcome them. In addition, applying some of these methods using commercial 50 nm thick SiNXmembranes with thick Si support frames, we printed arrays of holes in PMMA with pitches around 26 nm on SiNX/Si substrates with increasing Si thickness. Our results show that proximity effects from even 50 nm thick SiNXmembranes limit hole arrays to 20 nm pitch; however, down to this limit, the effect of the substrate thickness on the pattern quality is minimal. These results highlight the need for novel resists less susceptible to proximity effects, or resists which can be used directly, after development, as the dielectric material in periodic gates in 2D quantum devices.

Scalable Early Detection of Grapevine Viral Infection with Airborne Imaging Spectroscopy.

The U.S. wine and grape industry loses $3B annually due to viral diseases including grapevine leafroll-associated virus complex 3 (GLRaV-3). Current detection methods are labor-intensive and expensive. GLRaV-3 has a latent period in which the vines are infected but do not display visible symptoms, making it an ideal model to evaluate the scalability of imaging spectroscopy-based disease detection. The NASA Airborne Visible and Infrared Imaging Spectrometer Next Generation was deployed to detect GLRaV-3 in Cabernet Sauvignon grapevines in Lodi, CA in September 2020. Foliage was removed from the vines as part of mechanical harvest soon after image acquisition. In September of both 2020 and 2021, industry collaborators scouted 317 hectares on a vine-by-vine basis for visible viral symptoms and collected a subset for molecular confirmation testing. Symptomatic grapevines identified in 2021 were assumed to have been latently infected at the time of image acquisition. Random forest models were trained on a spectroscopic signal of noninfected and GLRaV-3 infected grapevines balanced with synthetic minority oversampling of noninfected and GLRaV-3 infected grapevines. The models were able to differentiate between noninfected and GLRaV-3 infected vines both pre- and postsymptomatically at 1 to 5 m resolution. The best-performing models had 87% accuracy distinguishing between noninfected and asymptomatic vines, and 85% accuracy distinguishing between noninfected and asymptomatic + symptomatic vines. The importance of nonvisible wavelengths suggests that this capacity is driven by disease-induced changes to plant physiology. The results lay a foundation for using the forthcoming hyperspectral satellite Surface Biology and Geology for regional disease monitoring in grapevine and other crop species. [Formula: see text] Copyright © 2023 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.