Human brain organoids provide unique platforms for modeling development and diseases by recapitulating the architecture of the embryonic brain. However, current organoid methods are limited by ...interior hypoxia and cell death due to insufficient surface diffusion, preventing generation of architecture resembling late developmental stages. Here, we report the sliced neocortical organoid (SNO) system, which bypasses the diffusion limit to prevent cell death over long-term cultures. This method leads to sustained neurogenesis and formation of an expanded cortical plate that establishes distinct upper and deep cortical layers for neurons and astrocytes, resembling the third trimester embryonic human neocortex. Using the SNO system, we further identify a critical role of WNT/β-catenin signaling in regulating human cortical neuron subtype fate specification, which is disrupted by a psychiatric-disorder-associated genetic mutation in patient induced pluripotent stem cell (iPSC)-derived SNOs. These results demonstrate the utility of SNOs for investigating previously inaccessible human-specific, late-stage cortical development and disease-relevant mechanisms.
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•SNOs maintain growth and laminar expansion over long-term culture•SNOs exhibit separated upper and deep cortical layers•Layer-specific WNT/β-catenin signaling regulates neuronal fate specification•DISC1 mutation causes deficits in cortical neuron fate specification
Cortical organoids can be used to model human brain development and disorders. Ming and colleagues overcome the diffusion limit using a slicing method to prevent interior cell death and sustain organoid growth over long-term culture. The resulting organoids recapitulate late-stage human cortical developmental features, including formation of distinct cortical layers.
A wide variety of oceanic and atmospheric phenomena are often observed in and around the sunglint region on optical images of the sea surface. The appearance of these phenomena depends strongly on ...the viewing geometry with areas on the sea surface that are rougher (or smoother) than the background appearing as either brighter or darker than the background depending on their position relative to the specular point. To understand these sea surface signature variations, this paper introduces the concept of a critical sensor viewing angle, defined as the sensor zenith angle at which different sea surface roughness variances produce identical sunglint radiance. It is when the imaging geometry transitions through the critical angle that a surface feature goes through a brightness reversal. Knowledge of where this transition takes place is important for properly interpreting the characteristics of the sea surface signature of these phenomena. The theory behind the concept of the critical angle is presented and then applied to sunglint imagery acquired over the ocean from space by the Moderate Resolution Imaging Spectroradiometer onboard NASA's Aqua and Terra satellites.
Immunohistochemistry (IHC) is a diagnostic technique used throughout pathology. A machine learning algorithm that could predict individual cell immunophenotype based on hematoxylin and eosin (H&E) ...staining would save money, time, and reduce tissue consumed. Prior approaches have lacked the spatial accuracy needed for cell-specific analytical tasks. Here IHC performed on destained H&E slides is used to create a neural network that is potentially capable of predicting individual cell immunophenotype. Twelve slides were stained with H&E and scanned to create digital whole slide images. The H&E slides were then destained, and stained with SOX10 IHC. The SOX10 IHC slides were scanned, and corresponding H&E and IHC digital images were registered. Color-thresholding and machine learning techniques were applied to the registered H&E and IHC images to segment 3,396,668 SOX10-negative cells and 306,166 SOX10-positive cells. The resulting segmentation was used to annotate the original H&E images, and a convolutional neural network was trained to predict SOX10 nuclear staining. Sixteen thousand three hundred and nine image patches were used to train the virtual IHC (vIHC) neural network, and 1,813 image patches were used to quantitatively evaluate it. The resulting vIHC neural network achieved an area under the curve of 0.9422 in a receiver operator characteristics analysis when sorting individual nuclei. The vIHC network was applied to additional images from clinical practice, and was evaluated qualitatively by a board-certified dermatopathologist. Further work is needed to make the process more efficient and accurate for clinical use. This proof-of-concept demonstrates the feasibility of creating neural network-driven vIHC assays.
Internal gravity waves, the subsurface analogue of the familiar surface gravity waves that break on beaches, are ubiquitous in the ocean. Because of their strong vertical and horizontal currents, and ...the turbulent mixing caused by their breaking, they affect a panoply of ocean processes, such as the supply of nutrients for photosynthesis, sediment and pollutant transport and acoustic transmission; they also pose hazards for man-made structures in the ocean. Generated primarily by the wind and the tides, internal waves can travel thousands of kilometres from their sources before breaking, making it challenging to observe them and to include them in numerical climate models, which are sensitive to their effects. For over a decade, studies have targeted the South China Sea, where the oceans' most powerful known internal waves are generated in the Luzon Strait and steepen dramatically as they propagate west. Confusion has persisted regarding their mechanism of generation, variability and energy budget, however, owing to the lack of in situ data from the Luzon Strait, where extreme flow conditions make measurements difficult. Here we use new observations and numerical models to (1) show that the waves begin as sinusoidal disturbances rather than arising from sharp hydraulic phenomena, (2) reveal the existence of >200-metre-high breaking internal waves in the region of generation that give rise to turbulence levels >10,000 times that in the open ocean, (3) determine that the Kuroshio western boundary current noticeably refracts the internal wave field emanating from the Luzon Strait, and (4) demonstrate a factor-of-two agreement between modelled and observed energy fluxes, which allows us to produce an observationally supported energy budget of the region. Together, these findings give a cradle-to-grave picture of internal waves on a basin scale, which will support further improvements of their representation in numerical climate predictions.
Celotno besedilo
Dostopno za:
DOBA, IJS, IZUM, KILJ, KISLJ, NUK, PILJ, PNG, SAZU, SBMB, SIK, UILJ, UKNU, UL, UM, UPUK
► We model changes in groundwater resources by the 2080s of a UK Chalk aquifer. ► We use outputs from 13 global climate models to drive a numerical groundwater model. ► Future climates simulations ...are based on an A2 greenhouse gas emissions scenario. ► Changes in the mean groundwater state variables are uncertain. ► The results suggest that the seasonal variation in the resource will be enhanced.
Projections of climate for the 2080s from an ensemble of global climate models (GCMs) run under a medium–high (A2) emissions scenario are used to simulate changes in groundwater resources of a Chalk aquifer in central-southern England. Few studies that have investigated the impacts of climate change on groundwater resources have addressed uncertainty. In this paper the uncertainty associated with use of a suite of GCM outputs in catchment scale impact studies is quantified. A range of predictions is obtained by applying precipitation and temperature change factors, derived from thirteen GCMs, to a distributed recharge model and a groundwater flow model of the Chalk aquifer of the Marlborough and Berkshire Downs and south-west Chilterns in the UK. The ensemble average suggests there will be a 4.9% reduction in annual potential groundwater recharge across the study area, although this is not statistically significant at the 95% confidence level. The spread of results for simulated changes in annual potential groundwater recharge range from a 26% decrease to a 31% increase by the 2080s, with ten predicting a decrease and three an increase. Whilst annual recharge is not found to change significantly, the multi-model results suggest that the seasonal variation in the groundwater resource will be greater, with higher recharge rates during a reduced period of time in winter. The spread of predictions for changes in river baseflow, at the bottom of the largest river sub-catchment, is from −16 to +33% in March and from −68 to −56% in October. The effects of climate change are shown to depend significantly on the type of land-use. It is concluded that further research is required to quantify the effect of different vegetation types on Chalk covered by different thicknesses of soil and their response to a changing climate.
Drawing on the social disorganization tradition and the social ecological perspective of Jane Jacobs, the authors hypothesize that neighborhoods composed of residents who intersect in space more ...frequently as a result of routine activities will exhibit higher levels of collective efficacy, intergenerational closure, and social network interaction and exchange. They develop this approach employing the concept of ecological networks—two-mode networks that indirectly link residents through spatial overlap in routine activities. Using data from the Los Angeles Family and Neighborhood Survey, they find evidence that econetwork extensity (the average proportion of households in the neighborhood to which a given household is tied through any location) and intensity (the degree to which household dyads are characterized by ties through multiple locations) are positively related to changes in social organization between 2000–2001 and 2006–2008. These findings demonstrate the relevance of econetwork characteristics—heretofore neglected in research on urban neighborhoods—for consequential dimensions of neighborhood social organization.
Safe and effective therapeutics for psychostimulant use disorders remain elusive. Deep brain stimulation (DBS), which is FDA-approved for other indications, is a promising candidate for treating ...severe substance use disorders. We examine the clinical and preclinical evidence for DBS of the nucleus accumbens as a possible therapeutic option for cocaine and methamphetamine use disorders. Limitations of the literature to date, including the lack of females included in studies evaluating the efficacy of DBS, and new strategies to optimize brain stimulation approaches are also discussed.
Context: Celiac disease (CD) prevalence and diagnosis have increased substantially in recent years. The current gold standard for CD confirmation is visual examination of duodenal mucosal biopsies. ...An accurate computer-aided biopsy analysis system using deep learning can help pathologists diagnose CD more efficiently. Subjects and Methods: In this study, we trained a deep learning model to detect CD on duodenal biopsy images. Our model uses a state-of-the-art residual convolutional neural network to evaluate patches of duodenal tissue and then aggregates those predictions for whole-slide classification. We tested the model on an independent set of 212 images and evaluated its classification results against reference standards established by pathologists. Results: Our model identified CD, normal tissue, and nonspecific duodenitis with accuracies of 95.3%, 91.0%, and 89.2%, respectively. The area under the receiver operating characteristic curve was >0.95 for all classes. Conclusions: We have developed an automated biopsy analysis system that achieves high performance in detecting CD on biopsy slides. Our system can highlight areas of interest and provide preliminary classification of duodenal biopsies before review by pathologists. This technology has great potential for improving the accuracy and efficiency of CD diagnosis.
Building on work defining the cocaine-modulated transcriptional landscape in mice, Godino and colleagues focus in this issue of Neuron1 on the role of a specific nuclear receptor, RXRα. Results ...demonstrate that modifying accumbens RXRα expression profoundly alters gene transcription, neuronal activity, and cocaine-induced behavioral responses.
Building on work defining the cocaine-modulated transcriptional landscape in mice, Godino and colleagues focus in this issue of Neuron1 on the role of a specific nuclear receptor, RXRα. Results demonstrate that modifying accumbens RXRα expression profoundly alters gene transcription, neuronal activity, and cocaine-induced behavioral responses.
This study integrates insights from social network analysis, activity space perspectives, and theories of urban and spatial processes to present an novel approach to neighborhood effects on ...health-risk behavior among youth. We suggest spatial patterns of neighborhood residents' non-home routines may be conceptualized as ecological, or “eco”-networks, which are two-mode networks that indirectly link residents through socio-spatial overlap in routine activities. We further argue structural configurations of eco-networks are consequential for youth's behavioral health. In this study we focus on a key structural feature of eco-networks – the neighborhood-level extent to which household dyads share two or more activity locations, or eco-network reinforcement – and its association with two dimensions of health-risk behavior, substance use and delinquency/sexual activity. Using geographic data on non-home routine activity locations among respondents from the Los Angeles Family and Neighborhood Survey (L.A.FANS), we constructed neighborhood-specific eco-networks by connecting sampled households to “activity clusters,” which are sets of spatially-proximate activity locations. We then measured eco-network reinforcement and examined its association with dimensions of adolescent health risk behavior employing a sample of 830 youth ages 12–17 nested in 65 census tracts. We also examined whether neighborhood-level social processes (collective efficacy and intergenerational closure) mediate the association between eco-network reinforcement and the outcomes considered. Results indicated eco-network reinforcement exhibits robust negative associations with both substance use and delinquency/sexual activity scales. Eco-network reinforcement effects were not explained by potential mediating variables. In addition to introducing a novel theoretical and empirical approach to neighborhood effects on youth, our findings highlight the importance of intersecting conventional routines for adolescent behavioral health.
•Neighborhood ecological networks link residents through routine activities.•Ecological network reinforcement protects against adolescent problem behavior.•Ecological network protective effects are comparable in disadvantaged neighborhoods.
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