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Abstract Iron stable isotopes (δ56Fe) are a useful tool for studying Earth processes, many of which involve redox transformations between Fe(III) and Fe(II). Here, we present two related experimental efforts, a study of the kinetic isotope effects (KIEs) associated with the reduction of Fe(III)‐ethylenediaminetetraacetic acid (EDTA) to Fe(II), and measurements of the biological fractionation of Fe isotopes by phytoplankton in culture. Reductants tested were ascorbate, hydroxylamine, Mn(II), dithionite, and photoreduction at pH between 5 and 9 and temperatures from 0 to 100°C. Isotope fractionations were very large, and included both normal and inverse KIEs, ranging from −4‰ to +5‰. Experiments were reproducible, yielding similar results for triplicate experiments run concurrently and for experiments run weeks apart. However, fractionations were not predictable, without a clear relationship to reaction rate, temperature, pH, or the reductant used. Acquisition of Fe by eukaryotic phytoplankton also often involves the reduction of Fe(III) to Fe(II). Several species of diatoms and a coccolithophore were tested for Fe isotope fractionation in culture using EDTA, NTA, and DFB as Fe(III) chelating ligands, yielding fractionations from −1.3‰ to +0.6‰. Biological isotope effects were also unpredictable, showing no clear relationship to species, growth rate, or Fe concentration. Variability in Fe isotope fractionation observed in culture may be explained in part by the sensitivity of KIEs. This work has implications for the industrial purification of isotopes, interpretation of natural δ56Fe, and the use of Fe isotopes as a tracer Fe source and biological processes in the ocean and other natural systems.

Background Women with chronic coronary disease are generally older than men and have more comorbidities but less atherosclerosis. We explored sex differences in revascularization, guideline‐directed medical therapy, and outcomes among patients with chronic coronary disease with ischemia on stress testing, with and without invasive management. Methods and Results The ISCHEMIA (International Study of Comparative Health Effectiveness with Medical and Invasive Approaches) trial randomized patients with moderate or severe ischemia to invasive management with angiography, revascularization, and guideline‐directed medical therapy, or initial conservative management with guideline‐directed medical therapy alone. We evaluated the primary outcome (cardiovascular death, myocardial infarction, or hospitalization for unstable angina, heart failure, or resuscitated cardiac arrest) and other end points, by sex, in 1168 (22.6%) women and 4011 (77.4%) men. Invasive group catheterization rates were similar, with less revascularization among women (73.4% of invasive‐assigned women revascularized versus 81.2% of invasive‐assigned men; P

Some anterior chambers do not readily shallow because of insufficient posterior pressure and/or very deep anterior chamber anatomy, which can make unscrolling descemet membrane endothelial keratoplasty (DMEK) tissue more challenging with an unmodified tap technique. We present a hands-free method for augmenting posterior pressure by temporarily tucking cellulose sponges under the blades of the eyelid speculum. The sponges transfer some of the eyelid speculum’s weight onto the bulbar surface posterior to the iris, thereby indenting the sclera and causing the iris diaphragm to bulge further forward. This hands-free technique can transform a potentially challenging DMEK case into a more straightforward one by facilitating both a shallow anterior chamber and a bimanual unscrolling technique. However, it only works in bicameral eyes with a vitreous body (e.g., an eye with penetrating keratoplasty, vitreous syneresis, and axial myopia) and will not work in unicameral eyes after vitrectomy (e.g., an eye with an Anterior Chamber Intraocular Lens (ACIOL)).

Cognition and attention arise from the adaptive coordination of neural systems in response to external and internal demands. The low-dimensional latent subspace that underlies large-scale neural dynamics and the relationships of these dynamics to cognitive and attentional states, however, are unknown. We conducted functional magnetic resonance imaging as human participants performed attention tasks, watched comedy sitcom episodes and an educational documentary, and rested. Whole-brain dynamics traversed a common set of latent states that spanned canonical gradients of functional brain organization, with global desynchronization among functional networks modulating state transitions. Neural state dynamics were synchronized across people during engaging movie watching and aligned to narrative event structures. Neural state dynamics reflected attention fluctuations such that different states indicated engaged attention in task and naturalistic contexts, whereas a common state indicated attention lapses in both contexts. Together, these results demonstrate that traversals along large-scale gradients of human brain organization reflect cognitive and attentional dynamics.

Abstract Psilocybin has shown promise for the treatment of mood disorders, which are often accompanied by cognitive dysfunction including cognitive rigidity. Recent studies have proposed neuropsychoplastogenic effects as mechanisms underlying the enduring therapeutic effects of psilocybin. In an open-label study of 24 patients with major depressive disorder, we tested the enduring effects of psilocybin therapy on cognitive flexibility (perseverative errors on a set-shifting task), neural flexibility (dynamics of functional connectivity or dFC via functional magnetic resonance imaging), and neurometabolite concentrations (via magnetic resonance spectroscopy) in brain regions supporting cognitive flexibility and implicated in acute psilocybin effects (e.g., the anterior cingulate cortex, or ACC). Psilocybin therapy increased cognitive flexibility for at least 4 weeks post-treatment, though these improvements were not correlated with the previously reported antidepressant effects. One week after psilocybin therapy, glutamate and N-acetylaspartate concentrations were decreased in the ACC, and dFC was increased between the ACC and the posterior cingulate cortex (PCC). Surprisingly, greater increases in dFC between the ACC and PCC were associated with less improvement in cognitive flexibility after psilocybin therapy. Connectome-based predictive modeling demonstrated that baseline dFC emanating from the ACC predicted improvements in cognitive flexibility. In these models, greater baseline dFC was associated with better baseline cognitive flexibility but less improvement in cognitive flexibility. These findings suggest a nuanced relationship between cognitive and neural flexibility. Whereas some enduring increases in neural dynamics may allow for shifting out of a maladaptively rigid state, larger persisting increases in neural dynamics may be of less benefit to psilocybin therapy.

Sustained attention (SA) and working memory (WM) are critical processes, but the brain networks supporting these abilities in development are unknown. We characterized the functional brain architecture of SA and WM in 9- to 11-year-old children and adults. First, we found that adult network predictors of SA generalized to predict individual differences and fluctuations in SA in youth. A WM model predicted WM performance both across and within children-and captured individual differences in later recognition memory-but underperformed in youth relative to adults. We next characterized functional connections differentially related to SA and WM in youth compared to adults. Results revealed 2 network configurations: a dominant architecture predicting performance in both age groups and a secondary architecture, more prominent for WM than SA, predicting performance in each age group differently. Thus, functional connectivity (FC) predicts SA and WM in youth, with networks predicting WM performance differing more between youths and adults than those predicting SA.

Abstract One major challenge to scaling quantum dot qubits is the dense wiring requirements, making it difficult to envision fabricating large 2D arrays of nearest-neighbor-coupled qubits necessary for error correction. We describe a method to ameliorate this issue by spacing out the qubits using superconducting resonators facilitated by 3D integration. To prove the viability of this approach, we use integration to couple an off-chip high-impedance TiN resonator to a double quantum dot in a Si/SiGe heterostructure. Using the resonator as a dispersive gate sensor, we tune the device down to the single electron regime with an SNR = 5.36. Characterizing the individual systems shows 3D integration can be done while maintaining low-charge noise for the quantum dots and high-quality factors for the superconducting resonator (single photon Q L = 2.14 × 104 with Q i ≈ 3 × 105), necessary for readout and high-fidelity two-qubit gates.

Resting-state functional connectivity (rsFC) measured with fMRI has been used to characterize functional brain maturation in typically and atypically developing children and adults. However, its reliability and utility for predicting development in infants and toddlers is less well understood. Here, we use fMRI data from the Baby Connectome Project study to measure the reliability and uniqueness of rsFC in infants and toddlers and predict age in this sample (8-to-26 months old; n = 170). We observed medium reliability for within-session infant rsFC in our sample, and found that individual infant and toddler’s connectomes were sufficiently distinct for successful functional connectome fingerprinting. Next, we trained and tested support vector regression models to predict age-at-scan with rsFC. Models successfully predicted novel infants’ age within ± 3.6 months error and a prediction R2 = .51. To characterize the anatomy of predictive networks, we grouped connections into 11 infant-specific resting-state functional networks defined in a data-driven manner. We found that connections between regions of the same network—i.e. within-network connections—predicted age significantly better than between-network connections. Looking ahead, these findings can help characterize changes in functional brain organization in infancy and toddlerhood and inform work predicting developmental outcome measures in this age range.

Objetivo. Informar sobre la oposición a las vacunas y la información errónea fomentadas en Twitter, destacando las cuentas de Twitter que dirigen estas conversaciones. Métodos. Utilizamos el aprendizaje automático supervisado para codificar todos los mensajes publicados en Twitter. En primer lugar, identificamos manualmente los códigos y los temas mediante un enfoque teórico fundamentado y, a continuación, los aplicamos a todo el conjunto de datos de forma algorítmica. Identificamos a los 50 autores más importantes un mes tras otro para determinar las fuentes influyentes de información relacionadas con la oposición a las vacunas. Resultados. El período de recopilación de datos fue del 1 de junio al 1 de diciembre del 2019, lo que dio lugar a 356 594 mensajes opuestos a las vacunas. Un total de 129 autores de Twitter reunieron los criterios de autor principal durante al menos un mes. Los autores principales fueron responsables del 59,5% de los mensajes opuestos a las vacunas y detectamos diez temas de conversación. Los temas se distribuyeron de forma similar entre los autores principales y todos los demás autores que declararon su oposición a las vacunas. Los autores principales parecían estar muy coordinados en su promoción de la información errónea sobre cada tema. Conclusiones. La salud pública se ha esforzado por responder a la información errónea sobre las vacunas. Los resultados indican que las fuentes de información errónea sobre las vacunas no son tan heterogéneas ni están tan distribuidas como podría parecer a primera vista, dado el volumen de mensajes. Existen fuentes identificables de información errónea, lo que puede ayudar a contrarrestar los mensajes y a fortalecer la vigilancia de la salud pública.

As public access to longitudinal developmental datasets like the Adolescent Brain Cognitive Development StudySM (ABCD Study®) increases, so too does the need for resources to benchmark time-dependent effects. Scan-to-scan changes observed with repeated imaging may reflect development but may also reflect practice effects, day-to-day variability in psychological states, and/or measurement noise. Resources that allow disentangling these time-dependent effects will be useful in quantifying actual developmental change. We present an accelerated adult equivalent of the ABCD Study dataset (a-ABCD) using an identical imaging protocol to acquire magnetic resonance imaging (MRI) structural, diffusion-weighted, resting-state and task-based data from eight adults scanned five times over five weeks. We report on the task-based imaging data (n = 7). In-scanner stop-signal (SST), monetary incentive delay (MID), and emotional n-back (EN-back) task behavioral performance did not change across sessions. Post-scan recognition memory for emotional n-back stimuli, however, did improve as participants became more familiar with the stimuli. Functional MRI analyses revealed that patterns of task-based activation reflecting inhibitory control in the SST, reward success in the MID task, and working memory in the EN-back task were more similar within individuals across repeated scan sessions than between individuals. Within-subject, activity was more consistent across sessions during the EN-back task than in the SST and MID task, demonstrating differences in fMRI data reliability as a function of task. The a-ABCD dataset provides a unique testbed for characterizing the reliability of brain function, structure, and behavior across imaging modalities in adulthood and benchmarking neurodevelopmental change observed in the open-access ABCD Study.

T1- and T2-weighted (T1w and T2w) images are essential for tissue classification and anatomical localization in Magnetic Resonance Imaging (MRI) analyses. However, these anatomical data can be challenging to acquire in non-sedated neonatal cohorts, which are prone to high amplitude movement and display lower tissue contrast than adults. As a result, one of these modalities may be missing or of such poor quality that they cannot be used for accurate image processing, resulting in subject loss. While recent literature attempts to overcome these issues in adult populations using synthetic imaging approaches, evaluation of the efficacy of these methods in pediatric populations and the impact of these techniques in conventional MR analyses has not been performed. In this work, we present two novel methods to generate pseudo-T2w images: the first is based in deep learning and expands upon previous models to 3D imaging without the requirement of paired data, the second is based in nonlinear multi-atlas registration providing a computationally lightweight alternative. We demonstrate the anatomical accuracy of pseudo-T2w images and their efficacy in existing MR processing pipelines in two independent neonatal cohorts. Critically, we show that implementing these pseudo-T2w methods in resting-state functional MRI analyses produces virtually identical functional connectivity results when compared to those resulting from T2w images, confirming their utility in infant MRI studies for salvaging otherwise lost subject data.

Interneuron subtypes have distinct properties and spatial distributions. Here, the authors show that the molecular-genetic basis of cortical resting-state brain function is shaped by distributions of interneuron-related transcripts and may capture individual differences in schizophrenia risk.

Abstract Background Physical activity is associated with reduced depression in youth and adults. However, our understanding of how different aspects of youth activities—specifically, the degree to which they are social, team-oriented, and physical—relate to mental health in children is less clear. Methods Here we use a data-driven approach to characterize the degree to which physical and non-physical youth activities are social and team-oriented. We then examine the relationship between depressive symptoms and participation in different clusters of youth activities using mixed effect models and causal mediation analyses in 11,875 children from the Adolescent Brain Cognitive Development (ABCD) Study. We test our hypotheses in an original sample (n = 4520, NDA release 1.1) and replication sample of participants (n = 7355, NDA release 2.0.1). Results We show and replicate that social–physical activities are associated with lower depressive symptoms. Next, we demonstrate that social connections, measured by number of close friends, partially mediate the association between social–physical activities and lower depressive symptoms. Conclusions Our results provide a rubric for using data-driven techniques to investigate different aspects of youth activities and highlight the social dynamics of physical activities as a possible protective factor against depression in childhood.

Although the feeling of being stressed is ubiquitous and clinically significant, the underlying neural mechanisms are unclear. Using a novel predictive modeling approach, the authors show that functional hippocampal networks specifically and consistently predict the feeling of stress.

Recent years have seen a surge of research on variability in functional brain connectivity within and between individuals, with encouraging progress toward understanding the consequences of this variability for cognition and behavior. At the same time, well-founded concerns over rigor and reproducibility in psychology and neuroscience have led many to question whether functional connectivity is sufficiently reliable, and call for methods to improve its reliability. The thesis of this opinion piece is that when studying variability in functional connectivity—both across individuals and within individuals over time—we should use behavior prediction as our benchmark rather than optimize reliability for its own sake. We discuss theoretical and empirical evidence to compel this perspective, both when the goal is to study stable, trait-level differences between people, as well as when the goal is to study state-related changes within individuals. We hope that this piece will be useful to the neuroimaging community as we continue efforts to characterize inter- and intra-subject variability in brain function and build predictive models with an eye toward eventual real-world applications.

Abstract Introduction Working memory is a critical cognitive ability that affects our daily functioning and relates to many cognitive processes and clinical conditions. Episodic memory is vital because it enables individuals to form and maintain their self‐identities. Our study analyzes the extent to which whole‐brain functional connectivity observed during completion of an N‐back memory task, a common measure of working memory, can predict both working memory and episodic memory. Methods We used connectome‐based predictive models (CPMs) to predict 502 Human Connectome Project (HCP) participants' in‐scanner 2‐back memory test scores and out‐of‐scanner working memory test (List Sorting) and episodic memory test (Picture Sequence and Penn Word) scores based on functional magnetic resonance imaging (fMRI) data collected both during rest and N‐back task performance. We also analyzed the functional brain connections that contributed to prediction for each of these models. Results Functional connectivity observed during N‐back task performance predicted out‐of‐scanner List Sorting scores and to a lesser extent out‐of‐scanner Picture Sequence scores, but did not predict out‐of‐scanner Penn Word scores. Additionally, the functional connections predicting 2‐back scores overlapped to a greater degree with those predicting List Sorting scores than with those predicting Picture Sequence or Penn Word scores. Functional connections with the insula, including connections between insular and parietal regions, predicted scores across the 2‐back, List Sorting, and Picture Sequence tasks. Conclusions Our findings validate functional connectivity observed during the N‐back task as a measure of working memory, which generalizes to predict episodic memory to a lesser extent. By building on our understanding of the predictive power of N‐back task functional connectivity, this work enhances our knowledge of relationships between working memory and episodic memory.

A group of scientists interested in history of science and fascinated by the figure of Nicolaus Steno (1638-1686) gathered in Florence for the 350th anniversary of the publication of his De solido intra solidum naturaliter contento prodromus dissertationis. A public conference held at Palazzo Fenzi on 16 October 2019 and a geological fieldtrip on the following day were occasions to discuss different points of view on the last published work of the Danish natural philosopher, dedicated to "solids naturally enclosed in other solids" (De solido intra solidum naturaliter contento, or De solido in short). The title of the gathering, "Galilean foundation for a solid earth", emphasized the philosophical context that Steno found in Florence, where in 1666-1668 he established tight human and philosophical bonds with renowned Italian disciples of Galileo Galilei and members of the Accademia del Cimento. For participants to the 2019 gathering, the Museum of Natural History of the University of Florence, hosting some of Steno's geological specimens, and the region of Tuscany itself, formed the perfect location to discuss the phenomena that Steno had observed from 1666-1668, the motivations for his research, the methodology of his discovery and, generally stated, the European scientific context which informed his inquiry. Some of the talks given in that meeting are included within this volume, kindly hosted by Substantia, International Journal of the History of Chemistry published by the Florence University Press. In addition some of the invited speakers who were unable to attend, also contributed a paper to this publication. The collection is about earth science in the early modern period, when the study of minerals, rocks, and the fossilized remains of living things did not yet form a distinct path to knowledge about earth history, but was an integral part of the wider "philosophy of nature".

Atmospheric aerosol particles are important for our planet's climate because they interact with radiation and clouds. Hence, having characterised methods to collect aerosol from aircraft for detailed offline analysis are valuable. However, collecting aerosol, particularly coarse-mode aerosol, onto substrates from a fast-moving aircraft is challenging and can result in both losses and enhancement in particles. Here we present the characterisation of an inlet system designed for collection of aerosol onto filters on board the Facility for Airborne Atmospheric Measurements (FAAM) BAe-146-301 Atmospheric Research Aircraft. We also present an offline scanning electron microscopy (SEM) technique for quantifying both the size distribution and size-resolved composition of the collected aerosol. We use this SEM technique in parallel with online underwing optical probes in order to experimentally characterise the efficiency of the inlet system. We find that the coarse-mode aerosol is sub-isokinetically enhanced, with a peak enhancement at around 10 µm up to a factor of 2 under recommended operating conditions. Calculations show that the efficiency of collection then decreases rapidly at larger sizes. In order to minimise the isokinetic enhancement of coarse-mode aerosol, we recommend sampling with total flow rates above 50 L min−1; operating the inlet with the bypass fully open helps achieve this by increasing the flow rate through the inlet nozzle. With the inlet characterised, we also present single-particle chemical information obtained from X-ray spectroscopy analysis, which allows us to group the particles into composition categories.

Mineral dust is an important component of the climate system, affecting the radiation balance, cloud properties, biogeochemical cycles, regional circulation and precipitation, as well as having negative effects on aviation, solar energy generation and human health. Dust size and composition has an impact on all these processes. However, changes in dust size distribution and composition during transport, particularly for coarse particles, are poorly understood and poorly represented in climate models. Here we present new in situ airborne observations of dust in the Saharan Air Layer (SAL) and the marine boundary layer (MBL) at the beginning of its transatlantic transport pathway, from the AERosol Properties – Dust (AER-D) fieldwork in August 2015, within the peak season of North African dust export. This study focuses on coarse-mode dust properties, including size distribution, mass loading, shape, composition, refractive indices and optical properties. Size distributions from 0.1 to 100 µm diameter (d) are presented, fully incorporating the coarse and giant modes of dust. Within the MBL, mean effective diameter (deff) and volume median diameter (VMD) were 4.6 and 6.0 µm respectively, giant particles with a mode at 20–30 µm were observed, and composition was dominated by quartz and alumino-silicates at d > 1 µm. Within the SAL, particles larger than 20 µm diameter were always present up to 5 km altitude, in concentrations over 10−5 cm−3, constituting up to 40 % of total dust mass. Mean deff and VMD were 4.0 and 5.5 µm respectively. Larger particles were detected in the SAL than can be explained by sedimentation theory alone. Coarse-mode composition was dominated by quartz and alumino-silicates; the accumulation mode showed a strong contribution from sulfate-rich and sea salt particles. In the SAL, measured single scattering albedos (SSAs) at 550 nm representing d d 2 g−1 (mean 0.32 m2 g−1). Variability in SSA was mainly controlled by variability in dust composition (principally iron) rather than by variations in the size distribution, in contrast with previous observations over the Sahara where size is the dominant influence. It is important that models are able to capture the variability and evolution of both dust composition and size distribution with transport in order to accurately represent the impacts of dust on climate. These results provide a new SAL dust dataset, fully representing coarse and giant particles, to aid model validation and development.

Cognitive states, such as rest and task engagement, share an 'intrinsic' functional network organization that is subject to minimal variation over time and yields stable signatures within an individual. Importantly, there are also transient state-specific functional connectivity (FC) patterns that vary across neural states. Here, we examine functional brain organization differences that underlie distinct states in a cross-sectional developmental sample. We compare FC fMRI data acquired during naturalistic viewing (i.e., movie-watching) and resting-state paradigms in a large cohort of 157 children and young adults aged 6–20. Naturalistic paradigms are commonly implemented in pediatric research because they maintain the child's attention and contribute to reduced head motion. It remains unknown, however, to what extent the brain-wide functional network organization is comparable during movie-watching and rest across development. Here, we identify a widespread FC pattern that predicts whether individuals are watching a movie or resting. Specifically, we develop a model for prediction of multilevel neural effects (termed PrimeNet), which can with high reliability distinguish between movie-watching and rest irrespective of age and that generalizes across movies. In turn, we characterize FC patterns in the most predictive functional networks for movie-watching versus rest and show that these patterns can indeed vary as a function of development. Collectively, these effects highlight a 'core' FC pattern that is robustly associated with naturalistic viewing, which also exhibits change across age. These results, focused here on naturalistic viewing, provide a roadmap for quantifying state-specific functional neural organization across development, which may reveal key variation in neurodevelopmental trajectories associated with behavioral phenotypes.