Macromolecular condensation organizes nucleolar sub-phases to set up a pH gradient.

Nucleoli are multicomponent condensates defined by coexisting sub-phases. We identified distinct intrinsically disordered regions (IDRs), including acidic (D/E) tracts and K-blocks interspersed by E-rich regions, as defining features of nucleolar proteins. We show that the localization preferences of nucleolar proteins are determined by their IDRs and the types of RNA or DNA binding domains they encompass. In vitro reconstitutions and studies in cells showed how condensation, which combines binding and complex coacervation of nucleolar components, contributes to nucleolar organization. D/E tracts of nucleolar proteins contribute to lowering the pH of co-condensates formed with nucleolar RNAs in vitro. In cells, this sets up a pH gradient between nucleoli and the nucleoplasm. By contrast, juxta-nucleolar bodies, which have different macromolecular compositions, featuring protein IDRs with very different charge profiles, have pH values that are equivalent to or higher than the nucleoplasm. Our findings show that distinct compositional specificities generate distinct physicochemical properties for condensates.

A multi-scale map of cell structure fusing protein images and interactions.

The cell is a multi-scale structure with modular organization across at least four orders of magnitude1. Two central approaches for mapping this structure-protein fluorescent imaging and protein biophysical association-each generate extensive datasets, but of distinct qualities and resolutions that are typically treated separately2,3. Here we integrate immunofluorescence images in the Human Protein Atlas4 with affinity purifications in BioPlex5 to create a unified hierarchical map of human cell architecture. Integration is achieved by configuring each approach as a general measure of protein distance, then calibrating the two measures using machine learning. The map, known as the multi-scale integrated cell (MuSIC 1.0), resolves 69 subcellular systems, of which approximately half are to our knowledge undocumented. Accordingly, we perform 134 additional affinity purifications and validate subunit associations for the majority of systems. The map reveals a pre-ribosomal RNA processing assembly and accessory factors, which we show govern rRNA maturation, and functional roles for SRRM1 and FAM120C in chromatin and RPS3A in splicing. By integration across scales, MuSIC increases the resolution of imaging while giving protein interactions a spatial dimension, paving the way to incorporate diverse types of data in proteome-wide cell maps.

Closed-loop network of skin-interfaced wireless devices for quantifying vocal fatigue and providing user feedback.

Vocal fatigue is a measurable form of performance fatigue resulting from overuse of the voice and is characterized by negative vocal adaptation. Vocal dose refers to cumulative exposure of the vocal fold tissue to vibration. Professionals with high vocal demands, such as singers and teachers, are especially prone to vocal fatigue. Failure to adjust habits can lead to compensatory lapses in vocal technique and an increased risk of vocal fold injury. Quantifying and recording vocal dose to inform individuals about potential overuse is an important step toward mitigating vocal fatigue. Previous work establishes vocal dosimetry methods, that is, processes to quantify vocal fold vibration dose but with bulky, wired devices that are not amenable to continuous use during natural daily activities; these previously reported systems also provide limited mechanisms for real-time user feedback. This study introduces a soft, wireless, skin-conformal technology that gently mounts on the upper chest to capture vibratory responses associated with vocalization in a manner that is immune to ambient noises. Pairing with a separate, wirelessly linked device supports haptic feedback to the user based on quantitative thresholds in vocal usage. A machine learning-based approach enables precise vocal dosimetry from the recorded data, to support personalized, real-time quantitation and feedback. These systems have strong potential to guide healthy behaviors in vocal use.

Analysis of the Human Protein Atlas Weakly Supervised Single-Cell Classification competition.

While spatial proteomics by fluorescence imaging has quickly become an essential discovery tool for researchers, fast and scalable methods to classify and embed single-cell protein distributions in such images are lacking. Here, we present the design and analysis of the results from the competition Human Protein Atlas - Single-Cell Classification hosted on the Kaggle platform. This represents a crowd-sourced competition to develop machine learning models trained on limited annotations to label single-cell protein patterns in fluorescent images. The particular challenges of this competition include class imbalance, weak labels and multi-label classification, prompting competitors to apply a wide range of approaches in their solutions. The winning models serve as the first subcellular omics tools that can annotate single-cell locations, extract single-cell features and capture cellular dynamics.

Dynamics of plosive consonants via imaging, computations, and soft electronics.

A quantitative understanding of the coupled dynamics of flow and particles in aerosol and droplet transmission associated with speech remains elusive. Here, we summarize an effort that integrates insights into flow-particle dynamics induced by the production plosive sounds during speech with skin-integrated electronic systems for monitoring the production of these sounds. In particular, we uncover diffusive and ballistic regimes separated by a threshold particle size and characterize the Lagrangian acceleration and pair dispersion. Lagrangian dynamics of the particles in the diffusive regime exhibit features of isotropic turbulence. These fundamental findings highlight the value in skin-interfaced wireless sensors for continuously measuring critical speech patterns in clinical settings, work environments, and the home, based on unique neck biomechanics associated with the generation of plosive sounds. We introduce a wireless, soft device that captures these motions to enable detection of plosive sounds in multiple languages through a convolutional neural network approach. This work spans fundamental flow-particle physics to soft electronic technology, with implications in monitoring and studying critical speech patterns associated with aerosol and droplet transmissions relevant to the spread of infectious diseases.

Characteristics of Myocardial Structure and Central Carbon Metabolism during the Early and Compensatory Stages of Cardiac Hypertrophy.

Cardiac hypertrophy is a classical forerunner of heart failure and myocardial structural and metabolic remodeling are closely associated with cardiac hypertrophy. We aim to investigate the characteristics of myocardial structure and central carbon metabolism of cardiac hypertrophy at different stages. Using echocardiography and pathological staining, early and compensatory cardiac hypertrophy were respectively defined as within 7 days and from 7 to 14 days after transverse aortic constriction (TAC) in mice. Among mass-spectrometry-based metabolomics, we identified 45 central carbon metabolites. Differential metabolite analysis showed that six metabolites, including citrate, cis-aconitate and so on, decreased significantly on day 1 after TAC. Ten metabolites, including l-lactate, (S)-2-hydroxyglutarate and so on, were obviously changed on days 10 and 14. Pathway analysis showed that these metabolites were involved in seven metabolic pathways, including carbohydrates, amino acids and so on. Western blot showed the expression of ATP-citrate lyase, malate dehydrogenase 1 and lactate dehydrogenase A in myocardium changed markedly on day 3, while the phosphorylation level of AMP-activated protein kinase did not show significantly difference. We hope our research will promote deeper understanding and early diagnosis of cardiac hypertrophy in clinical practice. All raw data were deposited in MetaboLights (MTBLS10555).

DeepImageJ: A user-friendly environment to run deep learning models in ImageJ.

DeepImageJ is a user-friendly solution that enables the generic use of pre-trained deep learning models for biomedical image analysis in ImageJ. The deepImageJ environment gives access to the largest bioimage repository of pre-trained deep learning models (BioImage Model Zoo). Hence, nonexperts can easily perform common image processing tasks in life-science research with deep learning-based tools including pixel and object classification, instance segmentation, denoising or virtual staining. DeepImageJ is compatible with existing state of the art solutions and it is equipped with utility tools for developers to include new models. Very recently, several training frameworks have adopted the deepImageJ format to deploy their work in one of the most used softwares in the field (ImageJ). Beyond its direct use, we expect deepImageJ to contribute to the broader dissemination and reuse of deep learning models in life sciences applications and bioimage informatics.

FISH-quant v2: a scalable and modular tool for smFISH image analysis.

Regulation of RNA abundance and localization is a key step in gene expression control. Single-molecule RNA fluorescence in situ hybridization (smFISH) is a widely used single-cell-single-molecule imaging technique enabling quantitative studies of gene expression and its regulatory mechanisms. Today, these methods are applicable at a large scale, which in turn come with a need for adequate tools for data analysis and exploration. Here, we present FISH-quant v2, a highly modular tool accessible for both experts and non-experts. Our user-friendly package allows the user to segment nuclei and cells, detect isolated RNAs, decompose dense RNA clusters, quantify RNA localization patterns and visualize these results both at the single-cell level and variations within the cell population. This tool was validated and applied on large-scale smFISH image data sets, revealing diverse subcellular RNA localization patterns and a surprisingly high degree of cell-to-cell heterogeneity.

Novel Insights into Sb(III) Oxidation and Immobilization during Ferrous Iron Oxygenation: The Overlooked Roles of Singlet Oxygen and Fe (oxyhydr)oxides Formation.

Reactive oxygen species (ROS) produced from the oxygenation of reactive Fe(II) species significantly affect the transformation of metalloids such as Sb at anoxic-oxic redox interfaces. However, the main ROS involved in Sb(III) oxidation and Fe (oxyhydr)oxides formation during co-oxidation of Sb(III) and Fe(II) are still poorly understood. Herein, this study comprehensively investigated the Sb(III) oxidation and immobilization process and mechanism during Fe(II) oxygenation. The results indicated that Sb(III) was oxidized to Sb(V) by the ROS produced in the aqueous and solid phases and then immobilized by formed Fe (oxyhydr)oxides via adsorption and coprecipitation. In addition, chemical analysis and extended X-ray absorption fine structure (EXAFS) characterization demonstrated that Sb(V) could be incorporated into the lattice structure of Fe (oxyhydr)oxides via isomorphous substitution, which greatly inhibited the formation of lepidocrocite (γ-FeOOH) and decreased its crystallinity. Notably, goethite (α-FeOOH) formation was favored at pH 6 due to the greater amount of incorporated Sb(V). Moreover, singlet oxygen (1O2) was identified as the dominant ROS responsible for Sb(III) oxidation, followed by surface-adsorbed ·OHads, ·OH, and Fe(IV). Our findings highlight the overlooked roles of 1O2 and Fe (oxyhydr)oxide formation in Sb(III) oxidation and immobilization during Fe(II) oxygenation and shed light on understanding the geochemical cycling of Sb coupled with Fe in redox-fluctuating environments.

Unveiling the Influence of Antimony Substitution on the Surface Properties and Adsorption Behavior of Ferrihydrite: From Molecular Mechanisms to Environmental Implications.

Antimony(V) substitution is common in secondary ferrihydrite, especially in mining areas and tailings. However, its impact on the adsorption behavior of ferrihydrite is still unclear. Therefore, this study investigated the influential mechanisms of Sb(V) substitution on the lattice structure and surface properties of Sb-substituted ferrihydrite (SbFh), and its adsorption of coexisting Sb(OH)6-. Antimony(V) is substituted at Fe1 sites and is primarily distributed on the surface. Substitution has opposing effects on the outer- and inner-sphere complexation of Sb(OH)6-. On one hand, substituted-Sb(V) transfers more positive charges to ≡FeOH, reducing the number of H bonds. Subsequently, the charge saturation of ≡FeOH decreases, surface charge increases, and outer-sphere complexation is promoted. On the other hand, the elevated bond valence of Sb-O increases charge saturation of ≡FeOH, reducing the charge capacity that ≡FeOH can accommodate from inner-sphere complexes. Thus, inner-sphere complexation is inhibited. Inner-sphere complexation plays a more important role, and Sb(OH)6- adsorption is inhibited. Additionally, the primary complexation modes of Sb(OH)6- transform from bidentate to monodentate complexation. This research has important implications for understanding the environmental behavior of ferrihydrite, as well as the fate and bioavailability of antimony in mining areas and tailings.

Automated, multiparametric monitoring of respiratory biomarkers and vital signs in clinical and home settings for COVID-19 patients.

Capabilities in continuous monitoring of key physiological parameters of disease have never been more important than in the context of the global COVID-19 pandemic. Soft, skin-mounted electronics that incorporate high-bandwidth, miniaturized motion sensors enable digital, wireless measurements of mechanoacoustic (MA) signatures of both core vital signs (heart rate, respiratory rate, and temperature) and underexplored biomarkers (coughing count) with high fidelity and immunity to ambient noises. This paper summarizes an effort that integrates such MA sensors with a cloud data infrastructure and a set of analytics approaches based on digital filtering and convolutional neural networks for monitoring of COVID-19 infections in sick and healthy individuals in the hospital and the home. Unique features are in quantitative measurements of coughing and other vocal events, as indicators of both disease and infectiousness. Systematic imaging studies demonstrate correlations between the time and intensity of coughing, speaking, and laughing and the total droplet production, as an approximate indicator of the probability for disease spread. The sensors, deployed on COVID-19 patients along with healthy controls in both inpatient and home settings, record coughing frequency and intensity continuously, along with a collection of other biometrics. The results indicate a decaying trend of coughing frequency and intensity through the course of disease recovery, but with wide variations across patient populations. The methodology creates opportunities to study patterns in biometrics across individuals and among different demographic groups.

Miniaturized wireless, skin-integrated sensor networks for quantifying full-body movement behaviors and vital signs in infants.

Early identification of atypical infant movement behaviors consistent with underlying neuromotor pathologies can expedite timely enrollment in therapeutic interventions that exploit inherent neuroplasticity to promote recovery. Traditional neuromotor assessments rely on qualitative evaluations performed by specially trained personnel, mostly available in tertiary medical centers or specialized facilities. Such approaches are high in cost, require geographic proximity to advanced healthcare resources, and yield mostly qualitative insight. This paper introduces a simple, low-cost alternative in the form of a technology customized for quantitatively capturing continuous, full-body kinematics of infants during free living conditions at home or in clinical settings while simultaneously recording essential vital signs data. The system consists of a wireless network of small, flexible inertial sensors placed at strategic locations across the body and operated in a wide-bandwidth and time-synchronized fashion. The data serve as the basis for reconstructing three-dimensional motions in avatar form without the need for video recordings and associated privacy concerns, for remote visual assessments by experts. These quantitative measurements can also be presented in graphical format and analyzed with machine-learning techniques, with potential to automate and systematize traditional motor assessments. Clinical implementations with infants at low and at elevated risks for atypical neuromotor development illustrates application of this system in quantitative and semiquantitative assessments of patterns of gross motor skills, along with body temperature, heart rate, and respiratory rate, from long-term and follow-up measurements over a 3-mo period following birth. The engineering aspects are compatible for scaled deployment, with the potential to improve health outcomes for children worldwide via early, pragmatic detection methods.

Comprehensive exercise reduces traumatic brain injury deficits via improving the neural network function of hippocampal CA1 and medial entorhinal cortex.

The present study aimed to investigate the alterations in functional interaction between hippocampal CA1 and medial entorhinal cortex (MEC) after moderate traumatic brain injury (TBI) in C57BL/6J mice, and the possible beneficial effects of comprehensive exercise (CE). Following TBI, two microelectrodes were implanted into CA1 and MEC for extracellular recording. We found a clear synchronization of neuronal firing in CA1 and MEC, particularly within 100 Hz and peaked at 20-30 Hz range. TBI induced a significant reduction (P < 0.001) of the coherences of firing between 20-40 Hz frequency band. The mean power spectral densities (PSD) of all group mice in MEC were steadily larger than the values in CA1 in both 20-40 Hz and 56-100 Hz ranges. TBI induced significant and consistent increases of averaged 20-40 Hz or 56-100 Hz PSD (P < 0.001 or P < 0.01) in both CA1 and MEC. Injured mice displayed more varied firing patterns, and showed increased burst frequency (BF), burst duration (BD), inter-spike intervals (ISI) and inter-burst interval (IBI). Injured mice also showed worsened neurological function, sleep, gait performance, and working memory. CE facilitated the restoration of aforementioned electrophysiological characteristics and functional deficits in TBI mice. These results suggest that the beneficial effects of CE on TBI functional deficits may be partly attributed to improved neuronal network interaction between CA1 and MEC.

Building the next generation of virtual cells to understand cellular biology.

Cell science has made significant progress by focusing on understanding individual cellular processes through reductionist approaches. However, the sheer volume of knowledge collected presents challenges in integrating this information across different scales of space and time to comprehend cellular behaviors, as well as making the data and methods more accessible for the community to tackle complex biological questions. This perspective proposes the creation of next-generation virtual cells, which are dynamic 3D models that integrate information from diverse sources, including simulations, biophysical models, image-based models, and evidence-based knowledge graphs. These virtual cells would provide statistically accurate and holistic views of real cells, bridging the gap between theoretical concepts and experimental data, and facilitating productive new collaborations among researchers across related fields.

Modified mouse model of repeated mild traumatic brain injury through a thinned-skull window and fluid percussion.

Mild traumatic brain injury (mTBI) is a clinically highly heterogeneous neurological disorder, none of the existing animal models can replicate the entire sequelae. This study aimed to develop a modified closed head injury (CHI) model of repeated mTBI (rmTBI) for investigating Ca2+ fluctuations of the affected neural network, the alternations of electrophysiology, and behavioral dysfunctions. The transcranial Ca2+ study protocol includes AAV-GCaMP6s infection in the right motor cortex, thinned-skull preparation, and two-photon laser scanning microscopy (TPLSM) imaging. The CHI rmTBI model is fabricated using the thinned-skull site and applying 2.0 atm fluid percussion with 48-h interval. The neurological dysfunction, minor motor performance, evident mood, spatial working, and reference deficits we found in this study mimic the clinically relevant syndromes after mTBI. Besides, our study revealed that there was a trend of transition from Ca2+ singlepeak to multipeak and plateau, and the total Ca2+ activities of multipeaks and plateaus (p < .001 vs. pre-rmTBI value) were significantly increased in ipsilateral layer 2/3 motor neurons after rm TBI. In parallel, there is a low-frequency power shift from delta to theta band (p < .01 vs. control) in the ipsilateral layer 2/3 of motor cortex of the rmTBI mice, and the overall firing rates significantly increased (p < .01 vs. control). Moreover, rmTBI causes slight cortical and hippocampal neuron damage and possibly induces neurogenesis in the dentate gyrus (DG). The alternations of Ca2+ and electrophysiological characteristics in layer 2/3 neuronal network, histopathological changes, and possible neurogenesis may play concertedly and partially contribute to the functional outcome post-rmTBI.

Publisher Correction: Analysis of the Human Protein Atlas Image Classification competition.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Author Correction: Analysis of the Human Protein Atlas Image Classification competition.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Publisher Correction: Analysis of the Human Protein Atlas Image Classification competition.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

OME-Zarr: a cloud-optimized bioimaging file format with international community support.

A growing community is constructing a next-generation file format (NGFF) for bioimaging to overcome problems of scalability and heterogeneity. Organized by the Open Microscopy Environment (OME), individuals and institutes across diverse modalities facing these problems have designed a format specification process (OME-NGFF) to address these needs. This paper brings together a wide range of those community members to describe the cloud-optimized format itself-OME-Zarr-along with tools and data resources available today to increase FAIR access and remove barriers in the scientific process. The current momentum offers an opportunity to unify a key component of the bioimaging domain-the file format that underlies so many personal, institutional, and global data management and analysis tasks.

FBXO6 regulates the antiviral immune responses via mediating alveolar macrophages survival.

Inducing early apoptosis in alveolar macrophages is one of the strategies influenza A virus (IAV) evolved to subvert host immunity. Correspondingly, the host mitochondrial protein nucleotide-binding oligomerization domain-like receptor (NLR)X1 is reported to interact with virus polymerase basic protein 1-frame 2 (PB1-F2) accessory protein to counteract virus-induced apoptosis. Herein, we report that one of the F-box proteins, FBXO6, promotes proteasomal degradation of NLRX1, and thus facilitates IAV-induced alveolar macrophages apoptosis and modulates both macrophage survival and type I interferon (IFN) signaling. We observed that FBXO6-deficient mice infected with IAV exhibited decreased pulmonary viral replication, alleviated inflammatory-associated pulmonary dysfunction, and less mortality. Analysis of the lungs of IAV-infected mice revealed markedly reduced leukocyte recruitment but enhanced production of type I IFN in Fbxo6-/- mice. Furthermore, increased type I IFN production and decreased viral replication were recapitulated in FBXO6 knockdown macrophages and associated with reduced apoptosis. Through gain- and loss-of-function studies, we found lung resident macrophages but not bone marrow-derived macrophages play a key role in the differences FBXO6 signaling pathway brings in the antiviral immune response. In further investigation, we identified that FBXO6 interacted with and promoted the proteasomal degradation of NLRX1. Together, our results demonstrate that FBXO6 negatively regulates immunity against IAV infection by enhancing the degradation of NLRX1 and thus impairs the survival of alveolar macrophages and antiviral immunity of the host.