Miracle-dz/UniFAR-FTUs huggingface dataset:
Hypoxia promotes osteogenesis via regulation of the mito-nuclear communication

Bone marrow mesenchymal stem cells (MSCs) reside in a hypoxic niche that maintains their differentiation potential. Several studies have highlighted the critical role of hypoxia (low oxygen concentration) in the regulation of stem cell function, reporting differentiation defects following a switch to normoxia (high oxygen concentration). However, the molecular events triggering changes in stem cell fate decisions in response to high oxygen remain elusive. Here, we study the impact of normoxia in the mito-nuclear communication, with regards to stem cell differentiation. We show that normoxia-cultured MSCs undergo profound transcriptional alterations which cause irreversible osteogenesis defects. Mechanistically, high oxygen promotes chromatin compaction and histone hypo-acetylation, particularly on promoters and enhancers of osteogenic genes. Although normoxia induces rewiring of metabolism, resulting in high acetyl-CoA levels, histone hypo-acetylation occurs due to trapping of acetyl-CoA inside mitochondria, likely due to lower CiC activity. Strikingly, restoring the cytosolic acetyl-CoA pool via acetate supplementation remodels the chromatin landscape and rescues the osteogenic defects. Collectively, our results demonstrate that the metabolism-chromatin-osteogenesis axis is heavily perturbed in response to high oxygen and identify CiC as a novel, oxygen-sensitive regulator of MSC function.
Dictionary learning for integrative, multimodal and scalable single-cell analysis

Mapping single-cell sequencing profiles to comprehensive reference datasets provides a powerful alternative to unsupervised analysis. However, most reference datasets are constructed from single-cell RNA-sequencing data and cannot be used to annotate datasets that do not measure gene expression. Here we introduce ‘bridge integration’, a method to integrate single-cell datasets across modalities using a multiomic dataset as a molecular bridge. Each cell in the multiomic dataset constitutes an element in a ‘dictionary’, which is used to reconstruct unimodal datasets and transform them into a shared space. Our procedure accurately integrates transcriptomic data with independent single-cell measurements of chromatin accessibility, histone modifications, DNA methylation and protein levels. Moreover, we demonstrate how dictionary learning can be combined with sketching techniques to improve computational scalability and harmonize 8.6 million human immune cell profiles from sequencing and mass cytometry experiments. Our approach, implemented in version 5 of our Seurat toolkit ( http://www.satijalab.org/seurat ), broadens the utility of single-cell reference datasets and facilitates comparisons across diverse molecular modalities. Reference mapping is extended beyond scRNA-seq to single-cell epigenetic and proteomic data.
Epigenetic signals that direct cell type–specific interferon beta response in mouse cells

Preexisting cell type–specific chromatin features represent an additional regulatory layer for interferon beta response and direct binding of STAT transcription factors and gene induction. The antiviral response induced by type I interferon (IFN) via the JAK-STAT signaling cascade activates hundreds of IFN-stimulated genes (ISGs) across human and mouse tissues but varies between cell types. However, the links between the underlying epigenetic features and the ISG profile are not well understood. We mapped ISGs, binding sites of the STAT1 and STAT2 transcription factors, chromatin accessibility, and histone H3 lysine modification by acetylation (ac) and mono-/tri-methylation (me1, me3) in mouse embryonic stem cells and fibroblasts before and after IFNβ treatment. A large fraction of ISGs and STAT-binding sites was cell type specific with promoter binding of a STAT1/2 complex being a key driver of ISGs. Furthermore, STAT1/2 binding to putative enhancers induced ISGs as inferred from a chromatin co-accessibility analysis. STAT1/2 binding was dependent on the chromatin context and positively correlated with preexisting H3K4me1 and H3K27ac marks in an open chromatin state, whereas the presence of H3K27me3 had an inhibitory effect. Thus, chromatin features present before stimulation represent an additional regulatory layer for the cell type–specific antiviral response. Graphical Abstract
Basolateral amygdala to insular cortex activity makes sign-tracking behavior insensitive to outcome value

Goal-tracking rats are sensitive to Pavlovian outcome devaluation while sign-tracking rats are devaluation insensitive. During outcome devaluation, goal-tracking (GT) rats flexibly modify responding to cues based on the current value of the associated outcome. However, sign-tracking (ST) rats rigidly respond to cues regardless of the current outcome value. Our prior study demonstrated disconnection of the basolateral amygdala (BLA) and anterior insular cortex (aIC) decreased both goal- and sign-tracking behaviors. Given the role of these regions in appetitive motivation and behavioral flexibility we predicted that disrupting BLA to aIC pathway during outcome devaluation would reduce flexibility in GT rats and reduce rigid appetitive motivation in ST rats. We inhibited the BLA to aIC pathway by infusing inhibitory DREADDs (hM4Di-mcherry) or control (mCherry) virus into the BLA and implanted cannulae into the aIC to inhibit BLA terminals using intracranial injections of clozapine N-oxide (CNO). After training, we used a within subject satiety-induced outcome devaluation procedure in which we sated rats on training pellets (devalued condition) or homecage chow (valued condition). All rats received bilateral CNO infusions into the aIC prior to brief non-reinforced test sessions. Contrary to our hypothesis, BLA-IC inhibition did not interfere with devaluation sensitivity in GT rats but did make ST behaviors sensitive to devaluation. Intermediate rats showed the opposite effect, showing rigid in responding to cues with BLA-aIC pathway inactivation. Together, these results demonstrate BLA-IC projections mediate tracking-specific Pavlovian devaluation sensitivity and highlights the importance of considering individual differences in Pavlovian approach when evaluating circuitry contributions to behavioral flexibility.
Distinct chromosomal “niches” in the genome of S. cerevisiae provide the background for genomic innovation and shape the fate of gene duplicates

Gene duplication is a major source of genomic innovation in all eukaryotes, with large proportions of genes being the result of either small-scale (SSD) or genome-wide duplication (WGD) events. In the model unicellular eukaryote Saccharomyces cerevisiae, of which nearly one third of the genome corresponds to gene duplicates, the two modes of duplication have been shown to follow different evolutionary fates, with SSD genes being more prone to acquire novel functionalities (neofunctionalization) and WGD more likely to retain different parts of the original ancestral function (subfunctionalization). Having previously described aspects of functional compartmentalization for the genes of S. cerevisiae, in this work we set out to investigate the existence of positional preferences of gene duplicates. We found that SSD and WGD genes are organized in distinct gene clusters that are, furthermore, segregated, occupying different regions, with SSD being more peripheral and WGD more centrally positioned close to centromeric chromatin. Duplicate gene clusters differ from the rest of the genome in terms of gene size and spacing, gene expression variability and regulatory complexity. What is more interesting, some of these properties are also shared by singleton genes residing in duplicate-rich regions in a position-dependent manner. Our analysis further reveals particular chromatin architectures in the promoters of duplicate genes, which are generally longer, with less pronounced nucleosome-free regions, strong structural constraints and a larger number of regulatory elements. Such structural features appear to be important for gene evolution as we find SSD gene-pair co-expression to be strongly associated with the similarity of nucleosome positioning patterns. We propose that specific regions of the yeast genome provide a favourable environment for the generation and maintenance of small-scale gene duplicates. The existence of such genomic “niches” is supported by the enrichment of these regions in singleton genes bearing similarities with gene “relics”, remnants of recent duplications that have reverted to single gene status. Our findings provide a valuable framework for the study of genomic innovation and suggest taking into account positional preferences in the study of gene emergence and fixation in experimentally and naturally evolving populations.
Conservation and Evolution of the Sporulation Gene Set in Diverse Members of the Firmicutes

Many members of the phylum Firmicutes (Bacillota) are capable of producing endospores, which enhance the survival of important Gram-positive pathogens that cause such diseases as anthrax, botulism, colitis, gas gangrene, and tetanus. We show that the core set of sporulation genes, defined previously through genome comparisons of several bacilli and clostridia, is conserved in a wide variety of sporeformers from several distinct lineages of Firmicutes. ABSTRACT The current classification of the phylum Firmicutes (new name, Bacillota) features eight distinct classes, six of which include known spore-forming bacteria. In Bacillus subtilis, sporulation involves up to 500 genes, many of which do not have orthologs in other bacilli and/or clostridia. Previous studies identified about 60 sporulation genes of B. subtilis that were shared by all spore-forming members of the Firmicutes. These genes are referred to as the sporulation core or signature, although many of these are also found in genomes of nonsporeformers. Using an expanded set of 180 firmicute genomes from 160 genera, including 76 spore-forming species, we investigated the conservation of the sporulation genes, in particular seeking to identify lineages that lack some of the genes from the conserved sporulation core. The results of this analysis confirmed that many small acid-soluble spore proteins (SASPs), spore coat proteins, and germination proteins, which were previously characterized in bacilli, are missing in spore-forming members of Clostridia and other classes of Firmicutes. A particularly dramatic loss of sporulation genes was observed in the spore-forming members of the families Planococcaceae and Erysipelotrichaceae. Fifteen species from diverse lineages were found to carry skin (sigK-interrupting) elements of different sizes that all encoded SpoIVCA-like recombinases but did not share any other genes. Phylogenetic trees built from concatenated alignments of sporulation proteins and ribosomal proteins showed similar topology, indicating an early origin and subsequent vertical inheritance of the sporulation genes. IMPORTANCE Many members of the phylum Firmicutes (Bacillota) are capable of producing endospores, which enhance the survival of important Gram-positive pathogens that cause such diseases as anthrax, botulism, colitis, gas gangrene, and tetanus. We show that the core set of sporulation genes, defined previously through genome comparisons of several bacilli and clostridia, is conserved in a wide variety of sporeformers from several distinct lineages of Firmicutes. We also detected widespread loss of sporulation genes in many organisms, particularly within the families Planococcaceae and Erysipelotrichaceae. Members of these families, such as Lysinibacillus sphaericus and Clostridium innocuum, could be excellent model organisms for studying sporulation mechanisms, such as engulfment, formation of the spore coat, and spore germination.
Blood SSR1: A Possible Biomarker for Early Prediction of Parkinson’s Disease

Parkinson’s disease (PD) is the second most common neurodegenerative disease associated with age. Early diagnosis of PD is key to preventing the loss of dopamine neurons. Peripheral-blood biomarkers have shown their value in recent years because of their easy access and long-term monitoring advantages. However, few peripheral-blood biomarkers have proven useful. This study aims to explore potential peripheral-blood biomarkers for the early diagnosis of PD. Three substantia nigra (SN) transcriptome datasets from the Gene Expression Omnibus (GEO) database were divided into a training cohort and a test cohort. We constructed a protein–protein interaction (PPI) network and a weighted gene co-expression network analysis (WGCNA) network, found their overlapping differentially expressed genes and studied them as the key genes. Analysis of the peripheral-blood transcriptome datasets of PD patients from GEO showed that three key genes were upregulated in PD over healthy participants. Analysis of the relationship between their expression and survival and analysis of their brain expression suggested that these key genes could become biomarkers. Then, animal models were studied to validate the expression of the key genes, and only SSR1 (the signal sequence receptor subunit1) was significantly upregulated in both animal models in peripheral blood. Correlation analysis and logistic regression analysis were used to analyze the correlation between brain dopaminergic neurons and SSR1 expression, and it was found that SSR1 expression was negatively correlated with dopaminergic neuron survival. The upregulation of SSR1 expression in peripheral blood was also found to precede the abnormal behavior of animals. In addition, the application of artificial intelligence technology further showed the value of SSR1 in clinical PD prediction. The three classifiers all showed that SSR1 had high predictability for PD. The classifier with the best prediction accuracy was selected through AUC and MCC to construct a prediction model. In short, this research not only provides potential biomarkers for the early diagnosis of PD but also establishes a possible artificial intelligence model for predicting PD.
Do You Feel Included? A Latent Profile Analysis of Inclusion in the Chinese Context

Although the importance of inclusion has been firmly supported by prior studies, the question of whether certain subgroups exist in the workplace whose members feel more or less included remains under-explored, limiting our understanding of how an inclusive workplace can be achieved. To address this gap, the current study conducted a latent profile analysis (LPA) to obtain evidence-based information regarding employees’ sense of inclusion in their organizations. Using a sample of 1,168 participants engaged in multiple industries in China, we identified three profiles of inclusion, with a largest proportion feeling a moderate level of inclusion (69.5%), a smaller proportion feeling a high level of inclusion (22.7%), and a tiny proportion feeling a low level of inclusion (7.8%). The three profiles differ significantly on key variables, demonstrating that the group feeling more included tends to be more aged and tenured, hold a higher educational degree, work in the high-tech sector, and come from a developed area. Such a group also shows more engagement in their work but less exhaustion, feels that they have more opportunities for development, and gains more support from colleagues and supervisors. Our findings point to the existence of subgroups of inclusion within the Chinese context and highlight the characteristics of these profiles, which in turn shed lights on how we can reach the goal of inclusion.
Labyrinthine Fistula in Cholesteatoma Patients: Outcomes of Partial Labyrinthectomy With “Underwater Technique” to Preserve Hearing

Labyrinthine fistula (LF) is one of the most important complications of cholesteatoma and is defined as an abnormal communication between the inner and the middle ear. This study aims to describe our experience with the partial labyrinthectomy evaluating the post-operative hearing results. Twenty-one patients who presented labyrinthine fistula in the semicircular canals were included in the present study. Hearing impairment was present in 48% of patients (10/21). A pre-operative assessment using the Gardner–Robertson hearing classification showed the following: 52%, Class I; and 48%, Class II. A post-surgical Gardner–Robertson hearing classification evidenced the following: 43%, Class I; and 57%, Class II. The presence of LF is usually considered a negative prognostic factor for hearing preservation. The key point of partial labyrinthectomy surgery is the preservation of structures, keeping them wet with Ringer's solution throughout the procedures, and not performing suction that is close to the opened LF. The bony labyrinth is drilled underwater without suction, removing the entire cholesteatoma matrix and quickly plugging the site before and after the LF. This faster plugging of the labyrinth makes it possible to preserve the peri-lymph and the endo-lymph fluid and the hearing function. This study showed that a partial labyrinthectomy is useful for maintaining serviceable hearing in patients with LF.
Structural Features of China's Industrial Pollution Inequality: A Spatial-Temporal Distribution Perspective

With growing concerns about the allocation inequality of environmental benefits and pollution, it is crucial to investigate whether a special characteristic of China’s environmental inequality has emerged. The present study aims to elucidate the regional spatial features of industrial pollution inequality (IPI) (waste gas, wastewater, and solid waste measured by the Theil index separately) and their relevance to national territorial space planning strategies. Furthermore, we make a novel attempt to develop an integrated framework that employs a developed-Kaya identity with the Logarithmic Mean Divisia Index method to uncover the driving force of IPI disparities. We make use of the data published recently by the provincial panel of China, during the period 2000–2015. Based on this information, we found notable spatial-temporal heterogeneity in China’s IPI, highly correlated to China’s core national territorial space planning strategy, the “T-shaped” spatial development strategy. The empirical results support the “structural features” hypothesis in IPI for China. In particular, the Coastal Region has a great edge in industrial pollution equality. In most provinces in the Inland Corridor along the Yangtze River, the trend of IPI has been alleviated to some extent. However, provinces further inland that are off-side the two axes of “T-shaped” spatial development strategy have to respond to the two-fold challenge of the exacerbated trend in IPI both within and between the regions. Our findings also indicate that the effect of technological inequality is the main driving force for IPI in the earlier stage of development. However, effects of economic inequality together with that of economic structure inequality manifest in the middle or transition period and the economic inequality effect is the determinant in the later stage of development. Additionally, contributions of size effect and inequality effect are changeable over development process, economic inequality effect outweighs the economic size effect for IPI in more developed districts or districts in higher developing phases. These findings may help the government incorporate environmental equality goals into regional policies and contribute to the emerging literature on environmental inequality.
Digital Spatial Profiling of Individual Glomeruli From Patients With Anti-Neutrophil Cytoplasmic Autoantibody-Associated Glomerulonephritis

We previously showed that the rupture of Bowman’s capsule (BC) promotes the progression of crescentic glomerulonephritis by enhancing the entry of CD8+ T cells into the glomeruli. In the present study, we utilized digital spatial profiling to simultaneously profile the altered abundances of the messenger RNA (mRNA) transcripts and proteins in the glomerular and periglomerular areas of four biopsy samples of anti-neutrophil cytoplasmic autoantibody-associated glomerulonephritis (ANCA-GN) and two biopsy specimens of minimal change disease (MCD) controls. The paraffin-embedded biopsy samples were stained with collagen IV, CD45, and SYTO 13 to distinguish the glomeruli with periglomerular infiltration but intact BC, with focal BC rupture, and with extensive rupture of BC and glomeruli without crescent formation and leukocytic infiltration in ANCA-GN. By assessing multiple discrete glomerular areas, we found that the transcript expression levels of the secreted phosphoprotein-1 and its receptor CD44 were upregulated significantly in the glomeruli with more severe ruptures of BC, and their expression levels correlated positively with the fibrotic markers. We also found that both alternative and classic complement pathways were activated in the glomeruli from patients with ANCA-GN. Furthermore, M1 macrophages were involved mostly in the early stage of BC rupture, while M2 macrophages were involved in the late stage and may contribute to the fibrosis process of the crescents. Finally, loss of glomerular cells in ANCA-GN was likely mediated by apoptosis. Our results show that digital spatial profiling allows the comparative analysis of the mRNA and protein profiles in individual glomeruli affected differently by the disease process and the identification of potential novel mechanisms in ANCA-GN.
Combined Single Cell Transcriptome and Surface Epitope Profiling Identifies Potential Biomarkers of Psoriatic Arthritis and Facilitates Diagnosis via Machine Learning

Early diagnosis of psoriatic arthritis (PSA) is important for successful therapeutic intervention but currently remains challenging due, in part, to the scarcity of non-invasive biomarkers. In this study, we performed single cell profiling of transcriptome and cell surface protein expression to compare the peripheral blood immunocyte populations of individuals with PSA, individuals with cutaneous psoriasis (PSO) alone, and healthy individuals. We identified genes and proteins differentially expressed between PSA, PSO, and healthy subjects across 30 immune cell types and observed that some cell types, as well as specific phenotypic subsets of cells, differed in abundance between these cohorts. Cell type-specific gene and protein expression differences between PSA, PSO, and healthy groups, along with 200 previously published genetic risk factors for PSA, were further used to perform machine learning classification, with the best models achieving AUROC ≥ 0.87 when either classifying subjects among the three groups or specifically distinguishing PSA from PSO. Our findings thus expand the repertoire of gene, protein, and cellular biomarkers relevant to PSA and demonstrate the utility of machine learning-based diagnostics for this disease.