Modeling fragment counts improves single-cell ATAC-seq analysis.

Single-cell ATAC sequencing coverage in regulatory regions is typically binarized as an indicator of open chromatin. Here we show that binarization is an unnecessary step that neither improves goodness of fit, clustering, cell type identification nor batch integration. Fragment counts, but not read counts, should instead be modeled, which preserves quantitative regulatory information. These results have immediate implications for single-cell ATAC sequencing analysis.

Squidpy: a scalable framework for spatial omics analysis.

Spatial omics data are advancing the study of tissue organization and cellular communication at an unprecedented scale. Flexible tools are required to store, integrate and visualize the large diversity of spatial omics data. Here, we present Squidpy, a Python framework that brings together tools from omics and image analysis to enable scalable description of spatial molecular data, such as transcriptome or multivariate proteins. Squidpy provides efficient infrastructure and numerous analysis methods that allow to efficiently store, manipulate and interactively visualize spatial omics data. Squidpy is extensible and can be interfaced with a variety of already existing libraries for the scalable analysis of spatial omics data.

The biomechanical signature of loss of consciousness: computational modelling of elite athlete head injuries.

Sports related head injuries can cause transient neurological events including loss of consciousness and dystonic posturing. However, it is unknown why head impacts that appear similar produce distinct neurological effects. The biomechanical effect of impacts can be estimated using computational models of strain within the brain. Here, we investigate the strain and strain rates produced by professional American football impacts that led to loss of consciousness, posturing or no neurological signs. We reviewed 1280 National Football League American football games and selected cases where the team's medical personnel made a diagnosis of concussion. Videos were then analysed for signs of neurological events. We identified 20 head impacts that showed clear video signs of loss of consciousness and 21 showing clear abnormal posturing. Forty-one control impacts were selected where there was no observable evidence of neurological signs, resulting in 82 videos of impacts for analysis. Video analysis was used to guide physical reconstructions of these impacts, allowing us to estimate the impact kinematics. These were then used as input to a detailed 3D high-fidelity finite element model of brain injury biomechanics to estimate strain and strain rate within the brain. We tested the hypotheses that impacts producing loss of consciousness would be associated with the highest biomechanical forces, that loss of consciousness would be associated with high forces in brainstem nuclei involved in arousal and that dystonic posturing would be associated with high forces in motor regions. Impacts leading to loss of consciousness compared to controls produced higher head acceleration (linear acceleration; 81.5 g ± 39.8 versus 47.9 ± 21.4; P = 0.004, rotational acceleration; 5.9 krad/s2 ± 2.4 versus 3.5 ± 1.6; P < 0.001) and in voxel-wise analysis produced larger brain deformation in many brain regions, including parts of the brainstem and cerebellum. Dystonic posturing was also associated with higher deformation compared to controls, with brain deformation observed in cortical regions that included the motor cortex. Loss of consciousness was specifically associated with higher strain rates in brainstem regions implicated in maintenance of consciousness, including following correction for the overall severity of impact. These included brainstem nuclei including the locus coeruleus, dorsal raphé and parabrachial complex. The results show that in head impacts producing loss of consciousness, brain deformation is disproportionately seen in brainstem regions containing nuclei involved in arousal, suggesting that head impacts produce loss of consciousness through a biomechanical effect on key brainstem nuclei involved in the maintenance of consciousness.

Disclosing Results of Tests for Covert Consciousness: A Framework for Ethical Translation.

The advent of neurotechnologies including advanced functional magnetic resonance imaging and electroencephalography to detect states of awareness not detectable by traditional bedside neurobehavioral techniques (i.e., covert consciousness) promises to transform neuroscience research and clinical practice for patients with brain injury. As these interventions progress from research tools into actionable, guideline-endorsed clinical tests, ethical guidance for clinicians on how to responsibly communicate the sensitive results they yield is crucial yet remains underdeveloped. Drawing on insights from empirical and theoretical neuroethics research and our clinical experience with advanced neurotechnologies to detect consciousness in behaviorally unresponsive patients, we critically evaluate ethical promises and perils associated with disclosing the results of clinical covert consciousness assessments and describe a semistructured approach to responsible data sharing to mitigate potential risks.

Photo- and Cobalt-Catalyzed Synthesis of Heterocycles via Cycloisomerization of Unactivated Olefins.

We report a general, intramolecular cycloisomerization of unactivated olefins with pendant nucleophiles. The reaction proceeds under mild conditions and tolerates ethers, esters, protected amines, acetals, pyrazoles, carbamates, and arenes. It is amenable to N-, O-, as well as C-nucleophiles, yielding a number of different heterocycles including, but not limited to, pyrrolidines, piperidines, oxazolidinones, and lactones. Use of both a benzothiazinoquinoxaline as organophotocatalyst and a Co-salen catalyst obviates the need for stoichiometric oxidant or reductant. We showcase the utility of the protocol in late-stage drug diversification and synthesis of several small natural products.

Intermolecular Organophotocatalytic Cyclopropanation of Unactivated Olefins.

Intermolecular cyclopropanation of mono-, di-, and trisubstituted olefins with α-bromo-ß-ketoesters and α-bromomalonates under organophotocatalysis is reported. The reaction displays broad functional group tolerance, including substrates bearing acids, alcohols, halides, ethers, ketones, nitriles, esters, amides, carbamates, silanes, stannanes, boronic esters, as well as arenes, and furnishes highly substituted cyclopropanes. The transformation may be performed in the presence of air and moisture with 0.5 mol % of a benzothiazinoquinoxaline as organophotocatalyst. Mechanistic investigations, involving Stern-Volmer quenching, quantum yield determination, and deuteration experiments, are carried out, and a catalytic cycle for the transformation is discussed.

Probing cell identity hierarchies by fate titration and collision during direct reprogramming.

Despite the therapeutic promise of direct reprogramming, basic principles concerning fate erasure and the mechanisms to resolve cell identity conflicts remain unclear. To tackle these fundamental questions, we established a single-cell protocol for the simultaneous analysis of multiple cell fate conversion events based on combinatorial and traceable reprogramming factor expression: Collide-seq. Collide-seq revealed the lack of a common mechanism through which fibroblast-specific gene expression loss is initiated. Moreover, we found that the transcriptome of converting cells abruptly changes when a critical level of each reprogramming factor is attained, with higher or lower levels not contributing to major changes. By simultaneously inducing multiple competing reprogramming factors, we also found a deterministic system, in which titration of fates against each other yields dominant or colliding fates. By investigating one collision in detail, we show that reprogramming factors can disturb cell identity programs independent of their ability to bind their target genes. Taken together, Collide-seq has shed light on several fundamental principles of fate conversion that may aid in improving current reprogramming paradigms.

Ultra-high sensitivity mass spectrometry quantifies single-cell proteome changes upon perturbation.

Single-cell technologies are revolutionizing biology but are today mainly limited to imaging and deep sequencing. However, proteins are the main drivers of cellular function and in-depth characterization of individual cells by mass spectrometry (MS)-based proteomics would thus be highly valuable and complementary. Here, we develop a robust workflow combining miniaturized sample preparation, very low flow-rate chromatography, and a novel trapped ion mobility mass spectrometer, resulting in a more than 10-fold improved sensitivity. We precisely and robustly quantify proteomes and their changes in single, FACS-isolated cells. Arresting cells at defined stages of the cell cycle by drug treatment retrieves expected key regulators. Furthermore, it highlights potential novel ones and allows cell phase prediction. Comparing the variability in more than 430 single-cell proteomes to transcriptome data revealed a stable-core proteome despite perturbation, while the transcriptome appears stochastic. Our technology can readily be applied to ultra-high sensitivity analyses of tissue material, posttranslational modifications, and small molecule studies from small cell counts to gain unprecedented insights into cellular heterogeneity in health and disease.

Epinephrine autoinjectors: individualizing device and dosage to optimize anaphylaxis management in the community setting.

Background: Anaphylaxis is the most severe manifestation of a systemic allergic reaction, and, in the community setting, the immediate administration of an epinephrine autoinjector (EAI) can be life-saving. Physicians are tasked with selecting the most appropriate EAI for each individual and counseling patients and/or their caregivers to maximize the likelihood of successful deployment of the EAI. Objective: To offer an evidence-based expert clinical perspective on how physicians might best tailor EAI selection to their patients with anaphylaxis. Methods: A group of eight adult and pediatric allergists with expertise in anaphylaxis management reviewed and assessed the published data and guidelines on anaphylaxis management and EAI device selection. Results: Personalized EAI selection is influenced by intrinsic individual factors, extrinsic factors such as the properties of the individual EAI (e.g., dose, needle length, overall design) as well as cost and coverage. The number and the variety of EAIs available have expanded in most jurisdictions in recent years, which provide a greater diversity of options to meet the characteristics and needs of patients with anaphylaxis. Conclusion: There currently are no EAIs with customizable dose and needle length. Although precise personalization of each patient's EAI remains an optimistic future aspiration, careful consideration of all variables when prescribing EAIs can support optimal management of anaphylaxis.

Concepts and limitations for learning developmental trajectories from single cell genomics.

Single cell genomics has become a popular approach to uncover the cellular heterogeneity of progenitor and terminally differentiated cell types with great precision. This approach can also delineate lineage hierarchies and identify molecular programmes of cell-fate acquisition and segregation. Nowadays, tens of thousands of cells are routinely sequenced in single cell-based methods and even more are expected to be analysed in the future. However, interpretation of the resulting data is challenging and requires computational models at multiple levels of abstraction. In contrast to other applications of single cell sequencing, where clustering approaches dominate, developmental systems are generally modelled using continuous structures, trajectories and trees. These trajectory models carry the promise of elucidating mechanisms of development, disease and stimulation response at very high molecular resolution. However, their reliable analysis and biological interpretation requires an understanding of their underlying assumptions and limitations. Here, we review the basic concepts of such computational approaches and discuss the characteristics of developmental processes that can be learnt from trajectory models.

Applications of Advanced MRI to Disorders of Consciousness.

Disorder of consciousness (DoC) after severe brain injury presents numerous challenges to clinicians, as the diagnosis, prognosis, and management are often uncertain. Magnetic resonance imaging (MRI) has long been used to evaluate brain structure in patients with DoC. More recently, advances in MRI technology have permitted more detailed investigations of the brain's structural integrity (via diffusion MRI) and function (via functional MRI). A growing literature has begun to show that these advanced forms of MRI may improve our understanding of DoC pathophysiology, facilitate the identification of patient consciousness, and improve the accuracy of clinical prognostication. Here we review the emerging evidence for the application of advanced MRI for patients with DoC.

2021 JOSA A Emerging Researcher Best Paper Prize: editorial.

JOSA A Editor-in-Chief, Olga Korotkova, Feature Editor, Johannes Courtial, and members of the 2021 Emerging Researcher Best Paper Prize Committee announce the recipient of the 2021 prize for the best paper published by an emerging researcher in the Journal.

BDNF rs6265 Genotype Influences Outcomes of Pharmacotherapy and Subthalamic Nucleus Deep Brain Stimulation in Early-Stage Parkinson's Disease.

INTRODUCTION: The efficacy of pharmacotherapy and deep brain stimulation of the subthalamic nucleus in treating Parkinson's disease motor symptoms is highly variable and may be influenced by patient genotype. The relatively common (prevalence about one in three) and protein-altering rs6265 single nucleotide polymorphism (C > T) in the gene BDNF has been associated with different clinical outcomes with levodopa. OBJECTIVE: We sought to replicate this reported association in early-stage Parkinson's disease subjects and to examine whether a difference in clinical outcomes was present with subthalamic nucleus deep brain stimulation. MATERIALS AND METHODS: Fifteen deep brain stimulation and 13 medical therapy subjects were followed for 24 months as part of the Vanderbilt DBS in Early Stage PD clinical trial (NCT00282152, FDA IDE #G050016). Primary outcome measures were the Unified Parkinson's Disease Rating Scale (UPDRS) and Parkinson's Disease Questionnaire-39. RESULTS: Outcomes with drug therapy in subjects carrying the rs6265 T allele were significantly worse following 12 months of treatment compared to C/C subjects (UPDRS: +20 points, p = 0.019; PDQ-39: +16 points, p = 0.018). In contrast, rs6265 genotype had no effect on overall motor response to subthalamic nucleus deep brain stimulation at any time point; further, rs6265 C/C subjects treated with stimulation were associated with worse UPDRS part II scores at 24 months compared to medical therapy. CONCLUSIONS: Genotyping for the rs6265 polymorphism may be useful for predicting long-term response to drug therapy and counseling Parkinson's disease patients regarding whether to consider earlier subthalamic nucleus deep brain stimulation. Validation in a larger cohort of early-stage Parkinson's disease subjects is warranted.

Volume replacement is associated with a diminished osmolar effect of mannitol in patients with acute brain injury.

INTRODUCTION: Animal experiments recently demonstrated that replacing urinary loses with crystalloid diminishes the therapeutic effect of mannitol by reducing the increase in osmolality. We aimed to investigate whether this effect is similarly seen in in brain-injured patients by studying the association between total body fluid balance (TBB) and the osmolar response to mannitol. METHODS: We performed a retrospective cohort study of adult patients with acute brain injury between 2015 and 2021 who received ≥ 2 doses of mannitol within 8 hours and no intercurrent concentrated saline solution. We analyzed the association between the change in TBB (∆TBB) and change in osmolality (∆Osm) before and after mannitol in a linear model, both as univariate and after adjustment for common confounding factors. RESULTS: Of 6,145 patients who received mannitol, 155 patients met inclusion criteria (mean age 60 ± 17 years, 48% male, 83% white). The mean total mannitol dose was 2 ± 0.5 g/kg and the mean change in plasma osmolality was 7.9 ± 7.1 mOsm/kg. Each 1 L increase in ∆TBB was associated with a change of -1.1 mOsm/L in ∆Osm (95% CI [-2.2, -0.02], p = 0.045). The magnitude of association was similar to that of total mannitol dose and remained consistent in an adjusted model and after excluding outliers. CONCLUSIONS: In patients with acute brain injury, a positive TBB is associated with a diminished mannitol-induced increase in plasma osmolality. Future prospective studies are needed to confirm these findings and their influence on the therapeutic effect of mannitol.

Automatic identification of relevant genes from low-dimensional embeddings of single-cell RNA-seq data.

MOTIVATION: Dimensionality reduction is a key step in the analysis of single-cell RNA-sequencing data. It produces a low-dimensional embedding for visualization and as a calculation base for downstream analysis. Nonlinear techniques are most suitable to handle the intrinsic complexity of large, heterogeneous single-cell data. However, with no linear relation between gene and embedding coordinate, there is no way to extract the identity of genes driving any cell's position in the low-dimensional embedding, making it difficult to characterize the underlying biological processes. RESULTS: In this article, we introduce the concepts of local and global gene relevance to compute an equivalent of principal component analysis loadings for non-linear low-dimensional embeddings. Global gene relevance identifies drivers of the overall embedding, while local gene relevance identifies those of a defined sub-region. We apply our method to single-cell RNA-seq datasets from different experimental protocols and to different low-dimensional embedding techniques. This shows our method's versatility to identify key genes for a variety of biological processes. AVAILABILITY AND IMPLEMENTATION: To ensure reproducibility and ease of use, our method is released as part of destiny 3.0, a popular R package for building diffusion maps from single-cell transcriptomic data. It is readily available through Bioconductor. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Predicting antigen specificity of single T cells based on TCR CDR3 regions.

It has recently become possible to simultaneously assay T-cell specificity with respect to large sets of antigens and the T-cell receptor sequence in high-throughput single-cell experiments. Leveraging this new type of data, we propose and benchmark a collection of deep learning architectures to model T-cell specificity in single cells. In agreement with previous results, we found that models that treat antigens as categorical outcome variables outperform those that model the TCR and antigen sequence jointly. Moreover, we show that variability in single-cell immune repertoire screens can be mitigated by modeling cell-specific covariates. Lastly, we demonstrate that the number of bound pMHC complexes can be predicted in a continuous fashion providing a gateway to disentangle cell-to-dextramer binding strength and receptor-to-pMHC affinity. We provide these models in the Python package TcellMatch to allow imputation of antigen specificities in single-cell RNA-seq studies on T cells without the need for MHC staining.

Intact Brain Network Function in an Unresponsive Patient with COVID-19.

Many patients with severe coronavirus disease 2019 (COVID-19) remain unresponsive after surviving critical illness. Although several structural brain abnormalities have been described, their impact on brain function and implications for prognosis are unknown. Functional neuroimaging, which has prognostic significance, has yet to be explored in this population. Here we describe a patient with severe COVID-19 who, despite prolonged unresponsiveness and structural brain abnormalities, demonstrated intact functional network connectivity, and weeks later recovered the ability to follow commands. When prognosticating for survivors of severe COVID-19, clinicians should consider that brain networks may remain functionally intact despite structural injury and prolonged unresponsiveness. ANN NEUROL 2020;88:851-854.

Force chains in crystalline and frustrated packing visualized by stress-birefringent spheres.

Force networks play an important role in the stability of configurations when granular material is packed into a container. These networks can redirect part of the weight of grains inside a container to the side walls. We employ monodisperse stress-birefringent spheres to visualize the contact forces in a quasi-2D and a nearly-2D configuration of these spheres in a thin cuboid cell. The packing structures are particularly simple: a hexagonal lattice in the ground state when the cell width is equal to the sphere diameter, and a frustrated, slightly distorted lattice in thicker cells. The force redistribution is substantially changed by this geometrical modification. In both cases, we observe an 'inverse' Janssen effect with the pressure decreasing from the top to the bottom of the container when the material is loaded with a weight on top of the vessel.

Fate of Environmental Proteins (eProteins) from Genetically Engineered Crops in Streams is Controlled by Water pH and Ecosystem Metabolism.

Environmental proteins (eProteins), such as Cry proteins associated with genetically engineered (GE) organisms, are present in ecosystems worldwide, but only rarely reach concentrations with detectable ecosystem-level impacts. Despite their ubiquity, the degradation and fate of Cry and other eProteins are mostly unknown. Here, we report the results of an experiment where we added Cry proteins leached from GE Bt maize to a suite of 19 recirculating experimental streams. We found that Cry exhibited a biphasic degradation with an initial phase of rapid and variable degradation within 1 h, followed by a slow and steady phase of degradation with traces of protein persisting after 48 h. The initial degradation was correlated with heterotrophic respiration and water column dissolved oxygen, confirming a previously documented association with stream metabolism. However, protein degradation persisted even with no biofilm and was faster at a more acidic pH, suggesting that water chemistry is also a critical factor in both degradation and subsequent detection. We suggest that Cry, as well as other eProteins, will have a rapid degradation caused by denaturation of proteins and pH changes, which confirms that the detection of Cry proteins in natural streams must be the result of steady and consistent leaching into the environment.

2020 JOSA A Emerging Researcher Best Paper Prize: editorial.

JOSA A Editor-in-Chief P. Scott Carney, Feature Editor Johannes Courtial, and members of the 2020 Emerging Researcher Best Paper Prize Committee announce the recipient of the 2020 prize for the best paper published by an emerging researcher in the Journal.