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At least 19 recordsLinked to original sources
PubMed1989

[Dietary preferences of domestic ruminants (cattle, sheep, goats) grazing on natural Sahelian and Sudano-Sahelian ranges. III. Epidermal characteristics of the principal plant species consumed on the pastures: compilation of a reference atlas with a view toward study of dietary preferences].

Microscopic analysis of vegetal fragments contained in the faeces and in the alimentary bolus is a method for studying the animals' diet on pastures. This work is conducted within the scope of a ruminant diet enquiry over Sahelian and Sudano-Sahelian pastures in Senegal. The author describes the epidermal characteristics of the main grazed plants (28 species) so as to constitute a reference atlas. An example of the identification key is exposed for 19 dicotyledons from their epidermal characteristics. This key will have to be completed and will help to recognize the plant debris contained in the faeces and in the alimentary bolus.

Animal Feed↗
PubMed2026

scATAnno: Automated Cell Type Annotation for Single-cell ATAC-seq Data.

Recent advances in single-cell epigenomic techniques have increased the demand for single-cell assay for transposase-accessible chromatin using sequencing (scATAC-seq) analysis. One key analytical task is to determine cell type identity based on epigenetic data. Here, we introduce scATAnno, a Python package designed to automatically annotate scATAC-seq data using large-scale scATAC-seq reference atlases. This workflow generates reference atlases from publicly available datasets, enabling accurate cell type annotation by integrating query data with reference atlases without the use of single-cell RNA sequencing (scRNA-seq) data. To enhance annotation accuracy, we incorporated k-nearest neighbors (KNN)-based and weighted distance-based uncertainty scores to effectively detect cell populations within the query data that are distinct from all cell types in the reference data. We compared and benchmarked scATAnno against five other published cell annotation approaches, demonstrating its superior performance across multiple datasets and metrics. We further showcased the utility of scATAnno across multiple datasets, including peripheral blood mononuclear cells (PBMCs), triple-negative breast cancer (TNBC), and basal cell carcinoma (BCC), and demonstrated that scATAnno accurately annotates cell types across diverse biological conditions. Overall, scATAnno is a useful tool for scATAC-seq reference atlas construction and cell type annotation and can facilitate the interpretation of new scATAC-seq datasets in complex biological systems. scATAnno is publicly available at https://scatanno-main.readthedocs.io/.

Single-Cell Analysis↗
PubMed2025

A general strategy for generating expert-guided, simplified views of ontologies.

Annotation of biomedical entities with widely used, well-structured ontologies and ontology-aware tools ensures data and analyses are Findable, Accessible, Interoperable, and Reusable (FAIR). Standardized terms with synonyms support lexical search, while ontology structure enables biologically meaningful grouping of annotations, such as by location and type. However, ontologies serving diverse communities are often more complex than needed for specific applications, creating barriers to adoption by researchers and resource developers. For example, cell atlases often attempt simplifications by manually building term hierarchies linking to cell type and anatomy ontologies, but these may include relationship types unsuitable for grouping annotations. We present tools for validating human expert curated term hierarchies, developed in two human reference atlas projects, against ontology structures. The tools provide tabular statistics plus graphical views of matching and non-matching terms and relationships to support discussion and conflict resolution. The HuBMAP Human Reference Atlas (HRA) effort is used to validate the approach and tools, and the Human Developmental Cell Atlas is featured as a use case.

Journal Article↗
PubMedDate not supplied

A computerized brain atlas: construction, anatomical content, and some applications.

An adjustable computerized atlas of the human brain has been developed, which can be adapted to fit individual anatomy. It is primarily intended for positron emission tomography (PET) but may also be used for single photon emission CT, transmission CT, magnetic resonance imaging, and neuroimaging-based procedures, such as stereotactic surgery and radiotherapy. The atlas is based on anatomical information obtained from brains fixed in situ soon after death. All structures have been drawn in on digitized photos of slices from one cryosectioned brain. The definition and classification of the anatomical structures and divisions are in agreement with the standard textbooks of anatomy, and the nomenclature is that of the Nomina Anatomica of 1965. The boundaries of the cortical cytoarchitectonic areas (Brodmann areas) have been determined using information from several sources, since three-dimensional literature data on their distribution are incomplete, scarce, and partly contradictory. However, no analysis of the cytoarchitectonics of the atlas brain itself has been undertaken. At present the data base contains three-dimensional representations of the brain surface, the ventricular system, the cortical gyri and sulci, as well as the Brodmann cytoarchitectonic areas. The major basal ganglia, the brain stem nuclei, the lobuli of the vermis, and the cerebellar hemispheres are also included. The computerized atlas can be used to improve the quantification and evaluation of PET data in several ways. For instance, it can serve as a guide in selecting regions of interest. It may also facilitate comparisons of data from different individuals or groups of individuals, by applying the inverse atlas transformation to PET data volume, thus relating the PET information to the anatomy of the reference atlas rather than to the patient's anatomy. Reformatted PET data from individuals can thus be averaged, and averages from different categories or different functional states of patients can be compared.

Anatomy, Artistic↗
PubMed1985

Bregma, lambda and the interaural midpoint in stereotaxic surgery with rats of different sex, strain and weight.

Craniometric and stereotaxic data from rats of different sex, strain and weight were compared. It was found that stereotaxic atlases can be used with rats of different sex and strain provided that the weights of the rats conform to those used in the reference atlas. If rats of different weights are used, greater accuracy can be achieved if bregma is used as the reference point for work with rostral structures and the interaural line for work with caudal structures.

Animals↗
PubMed1989

A computerized adjustable brain atlas.

A computerized brain atlas, adjustable to the patients anatomy, has been developed. It is primarily intended for use in positron emission tomography, but may also be employed in other fields utilizing neuro imaging, such as stereotactic surgery, transmission computerized tomography (CT) and magnetic resonance imaging (MRI). The atlas is based on anatomical information obtained from a digitized cryosectioned brain. It can be adjusted to fit a wide range of images from individual brains with normal anatomy. The corresponding transformation is chosen so that the modified atlas agrees with a set of CT or NMR images of the patient. The computerized atlas can be used to improve the quantification and evaluation of PET data by: Aiding and improving the selection of regions of interests. Facilitating comparisons of functional image data from different individuals or groups of individuals. Facilitating the comparison of different examinations of the same patient, thus reducing the need of reproducible fixation systems. Providing external a priori anatomical information to be used in the image reconstruction. Improving the attenuation and scatter corrections. Aiding in selecting a suitable patient orientation during the PET study. By applying the inverse atlas transformation to PET data set it is possible to relate the PET information to the anatomy of the reference atlas. Thus reformatted PET data from different patients can be averaged, and averages from different categories of patients can be compared. This procedure will facilitate the identification of statistically significant differences in the PET information from different groups of patients.

Brain↗
PubMed1986

Applications of a computerized adjustable brain atlas in positron emission tomography.

A computerized brain atlas, adjustable to the patient's anatomy, has been developed. It is primarily intended for use in positron emission tomography (PET), but may also be employed in other fields utilizing neuro-imaging, such as stereotactic surgery. The atlas is based on anatomic information obtained from digitized cryosectioned cadaver brains. It can be adjusted to fit a wide range of individual brains with reasonable accuracy. The corresponding transformation is chosen so that the modified atlas agrees with a set of CT or MR images of the patient. The computerized atlas can be used to facilitate and improve the quantification and evaluation of PET data by: enabling the merging and comparison of results from different individuals or groups of individuals; serving as a vehicle in the comparison of different examinations of the same patient, thus reducing the need of reproducible fixation systems; supplying external information to be used in the image reconstruction, such as proper three-dimensional regions of interest; improving the attenuation and scatter corrections; helping to select suitable patient orientation during the PET study. By applying the inverse atlas transformation to the PET data volume it is possible to relate the PET information to the anatomy of the reference atlas. Reformatted PET data from different patients can thus be averaged, and averages from different categories of patients can be compared. The method will facilitate the identification of statistically significant differences in the PET information from different groups of patients.

Brain↗
PubMed2026

Epigenetic Liquid Biopsy Enables Universal Mutation-Agnostic Molecular Surveillance for High-Risk Neuroblastoma.

PURPOSE: Liquid biopsy monitoring in pediatric solid tumors is limited by low mutational burden and lack of trackable genomic drivers. We sought to develop a mutation-agnostic, methylation-based liquid biopsy framework enabling universal molecular surveillance of high-risk neuroblastoma. EXPERIMENTAL DESIGN: Using whole-genome Oxford Nanopore Technologies sequencing of high-risk neuroblastoma tumors, we compared tumor-derived methylation profiles with a comprehensive atlas of normal human cell types and identified 72 neuroblastoma-specific differentially methylated regions (meNBL) that were reliably detectable in cell-free DNA (cfDNA). Marker robustness and specificity were validated using independent neuroblastoma methylation datasets and assessed against methylation profiles from other cancer types. We established neuroblastoma as a distinct methylation entity within the reference atlas by integrating a panel of 25 meNBLs, enabling quantitative estimation of tumor-derived cfDNA. Assay performance was evaluated across diagnostic, remission, relapse, and healthy control samples and compared with mutation-based and copy number-based approaches. RESULTS: Neuroblastoma-derived cfDNA was consistently detected at diagnosis and relapse but was absent in healthy controls and during confirmed remission. Methylation-based deconvolution demonstrated high specificity, with no detectable background signal in controls, and improved performance relative to copy number-based tumor fraction estimation. Longitudinal profiling enabled early molecular detection of relapse and reliable disease monitoring. CONCLUSIONS: We establish a robust, mutation-independent methylation-based liquid biopsy strategy for neuroblastoma that enables accurate, quantitative disease monitoring across all high-risk patients, including those lacking trackable genomic alterations. This approach supports the clinical translation of methylation-based cfDNA deconvolution as a broadly applicable platform for pediatric precision oncology.

Humans↗
PubMed2026

Unifying multimodal single-cell data with a mixture-of-experts β-variational autoencoder framework.

Multimodal single-cell assays profile complementary layers of cell state, but integration is complicated by modality mismatch, sparsity, and uneven cohort coverage. Here, we present Unified Variational Inference (UniVI), a scalable mixture-of-experts β-variational autoencoder that learns a shared latent space while preserving modality-specific structure. UniVI couples modality-specific encoders/decoders with a shared latent prior and a symmetric cross-modal alignment objective, enabling consistent integration of paired measurements without curated feature-link graphs or preannotated reference atlases; optional supervised heads can be added when labels are available. Across paired RNA-protein (CITE-seq) and RNA-chromatin (10x Genomics Multiome, SHARE-seq) data spanning human PBMCs and mouse back skin-a nonhematopoietic tissue with continuous differentiation hierarchies-UniVI produces coherent embeddings, improves label transfer, and enables cross-modal reconstruction and denoising. Extending to trimodal measurements, UniVI maintains robust three-way alignment among RNA, chromatin accessibility, and surface proteins (TEA-seq), and accommodates DNA methylation in a paired scNMT-seq mouse gastrulation proof-of-concept under beta-binomial likelihoods. Performance degrades gracefully under severe cell type imbalance and in the presence of modality-exclusive populations. In an acute myeloid leukemia mosaic design, a paired RNA-protein bridge anchors independent RNA-only and protein+genotype cohorts, revealing genotype-associated neighborhoods that sharpen with mutation-aware fine-tuning. UniVI thus provides a flexible, interpretable framework for multimodal integration across paired, trimodal, and mosaic study designs and supports practical reference-to-query projection in partially observed studies.

Journal Article↗
PubMed1977

Morphanalysis of craniofacial dysharmony.

The first stage in the morphanalysis of craniofacial dysharmony involves induction. In this process, individual analytic morphograms are combined to form analytic histograms, which in turn are connected to form analytic histomorphograms, which provide three-dimensional statements about the variation in craniofacial structures in a population. The second stage involves deduction, in which the analytic morphograms of a particular patient are compared with appropriate analytic histomorphograms, so that a diagnosis of the three-dimensional nature of the dysharmony can be made. Craniofacial morphanalysis is performed manually in small scale enquiries but the methods have been converted to computer-graphic technology for large-scale studies. A clinical morphanalysis service is currently conducted and a standard reference atlas is being prepared.

Adolescent↗
PubMed1992

The angiosomes of the mammals and other vertebrates.

This is a comparative study of the vasculature of the integument and underlying deep tissues of a range of mammals and other vertebrates. The investigation was conducted in the pig, monkey, dog, cat, possum, guinea pig, rat, rabbit, duck, and toad. The results from each are compared not only to each other, but also to previously performed human studies. The arterial network of the fresh animal cadaver was injected with a mixture of lead oxide and gelatin. The vascular anatomy of the skin, deep tissues, and individual muscles was defined by dissection, cutaneous perforator counts, photography, and radiography. A similar pilot study of the venous framework was performed in the pig, dog, and rabbit that included maps of the sites and orientations of the valves. The vasculature of the integument and deep tissues was correlated, and we found that we were able to define angiosomes (composite blocks of tissue supplied by the same source vessel) in each animal. Results revealed a marked dissimilarity of the overlying cutaneous vessels in many cases, yet a striking resemblance of the vascular architecture of the deep tissues. The size and density of the cutaneous perforators bore a close relation to the degree of the skin mobility, being large and sparse where the skin was mobile and smaller and more densely grouped where the integument was tethered or fixed. The cutaneous vasculature of the human resembled that of the monkey closely, was similar to that of the dog, cat, and possum, and was dissimilar to that of the pig, rat, guinea pig, and rabbit. Studies of the amphibian and bird bore many resemblances to those of the mammals. They provided basic concepts regarding modification of the animals' vascular anatomy in response to the functional demands of the species. In each animal, the arteries formed an unbroken network throughout the body. This consisted of anatomic territories linked by anastomotic vessels that were usually of reduced caliber. The pattern of the venous system was almost identical. Valved venous territories were linked by avalvular (oscillating) veins. The common denominator in the vascular system is the capillary bed. Conceptually, the anatomic arrangement of the arteries and veins, reproduced in each species, appears to be a sophisticated mechanism to allow equilibration of flow and pressure arriving at and departing from the capillary bed. The angiosome concept is reinforced by the animal studies. Although this investigation is essentially a detailed pilot study, it embraces many animals commonly used for experimentation and provides a reference atlas of their vasculature.(ABSTRACT TRUNCATED AT 400 WORDS)

Anatomy, Comparative↗
PubMed2026

A MAGIBU-based model for pediatric and juvenile CNS tumors: an in-house epigenetic decision-support framework compared with online DNA methylation classifiers.

Background: DNA methylation profiling is a tool that provides key support for central nervous system (CNS) tumor classification. However, diagnostically ambiguous pediatric cases may result in discordant outputs across classifiers. We developed MAGIBU, a cross-platform, projection-based framework that embeds individual methylomes into a fixed CNS reference landscape, ranking diagnostic entities by local epigenetic proximity to support clinician-led integrative diagnosis. Methods: As a proof-of-concept, we evaluated MAGIBU in eight morphologically challenging pediatric/juvenile CNS tumors with unresolved diagnoses after institutional and central pathology review. To establish a benchmark in the absence of a definitive histopathological ground truth, a consensus epigenetic reference was defined a priori for cases showing concordant results between the Heidelberg CNS Tumor Methylation Classifier and Methylscape Analysis. Comparisons were also performed with Epigenomic Digital Pathology (EpiDiP). To validate MAGIBU beyond this discovery cohort, performance was assessed at the family level across the CNS methylation spectrum (n = 678, 28 methylation families), on non-array platforms (whole-genome bisulfite sequencing and Oxford Nanopore), and in a focused analysis of the low-grade glioma and diffuse midline glioma compartment across four independent cohorts (n = 670). Results: In the discovery cohort, MAGIBU achieved high concordance with the consensus reference (Cohen's κ = 0.855), outperforming EpiDiP (κ = 0.278), which frequently placed low-grade tumors in proximity to higher-grade reference regions. Conclusions: MAGIBU provides a stable, quantitative differential diagnosis framework that mitigates the limitations of rigid categorical assignments. By leveraging a distance-based proximity metric, it offers a transparent decision-support tool that integrates effectively with clinical, radiological, and molecular data. While performance is inherently dependent on reference atlas composition, MAGIBU represents a robust complementary approach for the diagnostic workup of ambiguous CNS tumors.

Brain↗
PubMed2026

Reduced R-loop abundance at proinflammatory loci: a shared epigenetic mechanism in inflammatory and metabolic diseases.

INTRODUCTION: R-loops, RNA-DNA hybrid structures with a displaced single-stranded DNA loop, are key regulators of transcriptional control, chromatin architecture, and genome stability and have emerging roles in inflammatory signaling. However, the relationship between R-loop abundance and strongly modulated inflammatory effector genes in metabolic inflammation and influenza virus infection remains underexplored. METHODS: We performed a locus-centric integrative analysis combining robust differentially expressed genes (DEGs) from multiple inflammatory and infection-related murine and human transcriptomic disease models with experimentally validated multi-cell R-loop annotations from the reference atlas RLoopBase. Our correlation framework evaluated the directional relationship between R-loop abundance and inflammatory gene expression rather than assuming disease-sample-matched R-loop measurements. We further analyzed R-loop regulatory proteins, NRF2-associated R-loop regulators, and overlaps between R-loop regulators and CRISPRi-identified mitochondrial and cellular reactive oxygen species (ROS) regulators. RESULTS: In angiotensin II-infused apolipoprotein E-deficient (ApoE-/-) mice, a model of abdominal aortic aneurysm (AAA), genomic regions encoding the top significantly upregulated genes exhibited significantly fewer R-loops than those encoding downregulated genes at days 14 and 28. Similarly, in atherosclerotic ApoE-/- mice fed a high-fat diet for 32 and 78 weeks, upregulated genes were associated with fewer R-loops than downregulated genes. Reduced R-loop abundance was also observed in genomic regions encoding the top significantly upregulated genes in liver tissues from patients with non-alcoholic steatohepatitis (NASH), as well as in monosodium urate (MSU)-stimulated lymphatic endothelial cells (LECs) and influenza virus-infected human umbilical vein endothelial cells (HUVECs). R-loop regulatory proteins upregulated during metabolic inflammation were enriched in immune and inflammatory pathways. NRF2 was identified as a regulator of 27 R-loop regulatory proteins, including 10 positively and 17 negatively regulated proteins. Furthermore, 54 R-loop regulatory proteins overlapped with CRISPRi-identified mitochondrial and cellular ROS regulators, suggesting potential reciprocal regulation between R-loop homeostasis and ROS signaling. Disease-associated changes in pro-ROS and anti-ROS R-loop regulatory proteins further linked R-loop regulation to inflammatory and oxidative stress pathways. DISCUSSION: These findings identify reduced R-loop abundance at genomic regions encoding strongly upregulated inflammatory genes as a shared feature across multiple models of metabolic inflammation and influenza virus infection. The results further suggest that immune-associated R-loop regulatory proteins and the NRF2-ROS axis may contribute to R-loop remodeling during inflammatory disease. This integrative framework provides new insight into the potential role of R-loops and ROS-sensitive R-loop regulators in inflammatory and metabolic diseases and identifies candidate pathways for future mechanistic investigation and therapeutic targeting.

R-loop regulatory proteins↗
PubMed2025

Multi-omics analysis reveals distinct spatial compartmentalization of lung repair niches in pediatric ARDS.

BACKGROUND: Pediatric acute respiratory distress syndrome (PARDS), often triggered by viral infections, is a life-threatening condition. Despite its severity, children demonstrate significantly better survival rates and superior lung repair compared to adults. However, the mechanisms underlying this age-specific advantage remain incompletely understood. PATIENTS AND METHODS: We conducted a pilot multi-omics study of influenza-associated PARDS integrating single-cell RNA sequencing (scRNA-seq) of pediatric lung tissue and bronchoalveolar lavage fluid (BALF), spatial transcriptomics, and plasma proteomics. Analyses were harmonized with the Human Lung Cell Atlas (HLCA) reference, reanalysis of public pediatric PARDS airway scRNA-seq, and contextual comparisons to adult lethal COVID-19 lung. RESULTS: Tissue scRNA-seq and spatial data indicated outcome-linked divergence in PARDS. Survivor showed spatially restricted repair with preserved alveolar type II (AT2) cells, AT2-to-alveolar type I (AT1) differentiation signatures, and higher KRT17, whereas fatal case and adults exhibited diffuse immune activation with pro-fibrotic and pro-apoptotic signaling. In BALF, KRT17-positive airway stress–repair epithelial cells (hillock-like) increased from the acute to recovery phase, and plasma proteomics showed higher circulating KRT17 in survivors. HLCA-based label transfer strengthened cell-type definitions and enabled pediatric–adult comparisons suggesting biological and developmental differences; the adult lethal COVID-19 atlas provided a benchmark with attenuated epithelial repair and prominent collagen CTHRC1-pathologic fibroblasts. Fibroblast programs were regionally compartmentalized, with injury-enriched CTHRC1+ states versus alveolar fibroblasts in preserved areas, and showed stronger injury–homeostasis anti-correlation in fatalities. Myeloid remodeling included BALF transitions from FCN1-high inflammatory states toward FABP4-positive resident-like states, consistent with public pediatric datasets showing reduced inflammatory and interferon-stimulated gene (ISG) modules and severity-linked increases in aged neutrophils. CONCLUSIONS: This pilot multi-omics case series outlines putative pediatric lung repair niches in influenza-associated PARDS. KRT17-positive transitional epithelium, preserved AT2 differentiation, and restoration of resident-like macrophages may align with recovery, whereas diffuse immune activation and CTHRC1-enriched fibroblast programs may accompany worse outcomes. HLCA-guided annotations and adult benchmarks indicate possible age-related differences, warranting validation in larger multi-center cohorts.

Humans↗
PubMed2026

SCMO: a deep learning model integrating the single-cell resolution TME ecosystem and multi-omics for survival prediction in CRC patients.

BACKGROUND: Colorectal cancer (CRC) remains a leading cause of global cancer mortality, highlighting the need for precise survival prediction to guide clinical decisions. Although tissue-level multi-omics is widely utilized for survival prediction, its limited resolution cannot capture tumor heterogeneity. Single-cell RNA sequencing (scRNA-seq) enables dissection of the tumor microenvironment (TME) at cellular resolution, supporting personalized prognostic assessment. METHODS: We collected 213 CRC scRNA-seq samples and established a CRC-specific TME atlas comprising 339,060 cells. Using this atlas as a reference, we deconvolved bulk RNA-seq data from TCGA-CRC cohort with the EcoTyper algorithm to reconstruct TME features. Clinical, genomic, and transcriptomic data were obtained from the Xena platform; microbial data were sourced from the BIC database. We integrated TME and multi-omics features through a self-normalizing neural network to construct a deep learning model (single-cell resolution TME ecosystem with multi-omics data [SCMO]) for survival prediction. To enhance interpretability, we utilized the Integrated Gradients algorithm and spatial transcriptomic data to analyze multi-omics and TME features. We performed anticancer drug screening with tumor necrosis factor receptor-associated protein 1 (TRAP1), a critical feature according to the Integrated Gradients algorithm, as a potential target. RESULTS: We identified 13 survival-related TME features from the CRC-specific atlas: 12 cell states and one multi-cellular ecosystem. SCMO, which combined TME and multi-omics features, improved survival prediction and outperformed existing methods, achieving a concordance index of 0.762. The SCMO demonstrated robust performance for long-term predictions, achieving areas under the curve (AUCs) of 0.752, 0.772, and 0.869 for 1-, 3-, and 5-year predictions in the training set, with corresponding test set AUCs of 0.639, 0.756, and 0.772. TME features from the SCMO model revealed that ecosystem density increased with CRC malignancy. Multi-omics features included TRAP1 as a potential drug target. Drug screening identified saikosaponin A as a novel TRAP1 inhibitor, and its anticancer activity was validated in vitro. We developed SCMO-Lite, a simplified model incorporating 12 high-attribution-weight multi-omics features, which demonstrated robust risk stratification. CONCLUSIONS: SCMO combines analytical precision with biological interpretability, offering novel insights for oncology survival prediction.

Humans↗
PubMed2024

SIMS: A deep-learning label transfer tool for single-cell RNA sequencing analysis.

Cell atlases serve as vital references for automating cell labeling in new samples, yet existing classification algorithms struggle with accuracy. Here we introduce SIMS (scalable, interpretable machine learning for single cell), a low-code data-efficient pipeline for single-cell RNA classification. We benchmark SIMS against datasets from different tissues and species. We demonstrate SIMS's efficacy in classifying cells in the brain, achieving high accuracy even with small training sets (<3,500 cells) and across different samples. SIMS accurately predicts neuronal subtypes in the developing brain, shedding light on genetic changes during neuronal differentiation and postmitotic fate refinement. Finally, we apply SIMS to single-cell RNA datasets of cortical organoids to predict cell identities and uncover genetic variations between cell lines. SIMS identifies cell-line differences and misannotated cell lineages in human cortical organoids derived from different pluripotent stem cell lines. Altogether, we show that SIMS is a versatile and robust tool for cell-type classification from single-cell datasets.

Single-Cell Analysis↗
PubMed1977

Radiographs.

Physicians performing radiology for children should utilize modern equipment, expose children to the least amount of radiation possible, and avoid unnecessary examinations. Those interpreting radiographs must be familiar with the wide range of normal variations of the skeleton and/or be prepared to refer to texts and atlases dealing with these. Careful examination of soft tissues greatly increases the accuracy of diagnostic radiology in the search for trauma and infection.

Bone Diseases↗
PubMed2026

ERGA-BGE reference genome of Eunicella cavolini, an IUCN Near Threatened Gorgonian of the Mediterranean Sea.

The Eunicella cavolini reference genome provides an important resource to study the adaptation of this species to different environments and anthropic pressures. This species is impacted by human activities, including climate change, and this reference genome will be useful to study the genomic evolution of this species. The entirety of the genome sequence was assembled into 17 contiguous chromosomal pseudomolecules. This chromosome-level assembly encompasses 0.49 Gb, composed of 159 contigs and 46 scaffolds, with contig and scaffold N50 values of 7.7&#xa0;Mb and 51.1&#xa0;Mb, respectively.

Biodiversity Genomics Europe↗