Asherman’s Syndrome is characterized by intrauterine adhesions or scarring, which cause infertility, menstrual abnormalities, and recurrent pregnancy loss. The pathophysiology of this syndrome remains unknown, with treatment restricted to recurrent surgical removal of intrauterine scarring, which has limited success. Here, we decode the Asherman’s Syndrome endometrial cell niche by analyzing data from over 200,000 cells with single-cell RNA-sequencing in patients with this condition and through in vitro analyses of Asherman’s Syndrome patient-derived endometrial organoids. Our endometrial atlas highlights the loss of the endometrial epithelium, alterations to epithelial differentiation signaling pathways such as Wnt and Notch, and the appearance of characteristic epithelium expressing secretory leukocyte protease inhibitor during the window of implantation. We describe syndrome-associated alterations in cell-to-cell communication and gene expression profiles that support a dysfunctional pro-fibrotic, pro-inflammatory, and anti-angiogenic environment.
Chronic alcohol abuse causes an inflammatory response in the intestinal tract with damage to the integrity of the mucosa and epithelium, as well as dysbiosis in the gut microbiome. However, the role of gut bacteria in ethanol effects and how these microorganisms interact with the immune system are not well understood. The aim of the present study was to evaluate if TLR4 alters the ethanol-induced intestinal inflammatory response, and whether the response of this receptor affects the gut microbiota profile. We analyzed the 16S rRNA sequence of the fecal samples from wild-type (WT) and TLR4-knockout (TLR4-KO) mice with and without ethanol intake for 3 months. The results demonstrated that chronic ethanol consumption reduces microbiota diversity and causes dysbiosis in WT mice. Likewise, ethanol upregulates several inflammatory genes (IL-1β, iNOS, TNF-α) and miRNAs (miR-155-5p, miR-146a-5p) and alters structural and permeability genes (INTL1, CDH1, CFTR) in the colon of WT mice. Our results further demonstrated that TLR4-KO mice exhibit a different microbiota that can protect against the ethanol-induced activation of the immune system and colon integrity dysfunctions. In short, our results reveal that TLR4 is a key factor for determining the gut microbiota, which can participate in dysbiosis and the inflammatory response induced by alcohol consumption.
Endometrial decidualization resistance (DR) is implicated in various gynecological and obstetric conditions. Here, using a multi-omic strategy, we unraveled the cellular and molecular characteristics of DR in patients who have suffered severe preeclampsia (sPE). Morphological analysis unveiled significant glandular anatomical abnormalities, confirmed histologically and quantified by the digitization of hematoxylin and eosin-stained tissue sections. Single-cell RNA sequencing (scRNA-seq) of endometrial samples from patients with sPE (n = 11) and controls (n = 12) revealed sPE-associated shifts in cell composition, manifesting as a stromal mosaic state characterized by proliferative stromal cells (MMP11 and SFRP4) alongside IGFBP1+ decidualized cells, with concurrent epithelial mosaicism and a dearth of epithelial–stromal transition associated with decidualization. Cell–cell communication network mapping underscored aberrant crosstalk among specific cell types, implicating crucial pathways such as endoglin, WNT and SPP1. Spatial transcriptomics in a replication cohort validated DR-associated features. Laser capture microdissection/mass spectrometry in a second replication cohort corroborated several scRNA-seq findings, notably the absence of stromal to epithelial transition at a pathway level, indicating a disrupted response to steroid hormones, particularly estrogens. These insights shed light on potential molecular mechanisms underpinning DR pathogenesis in the context of sPE.
Background: Medical texts such as radiology reports or electronic health records are a powerful source of data for researchers. Anonymization methods must be developed to de-identify documents containing personal information from both patients and medical staff. Although currently there are several anonymization strategies for the English language, they are also language-dependent. Here, we introduce a named entity recognition strategy for Spanish medical texts, translatable to other languages. Results: We tested 4 neural networks on our radiology reports dataset, achieving a recall of 97.18% of the identifying entities. Alongside, we developed a randomization algorithm to substitute the detected entities with new ones from the same category, making it virtually impossible to differentiate real data from synthetic data. The three best architectures were tested with the MEDDOCAN challenge dataset of electronic health records as an external test, achieving a recall of 69.18%. Conclusions: The strategy proposed, combining named entity recognition tasks with randomization of entities, is suitable for Spanish radiology reports. It does not require a big training corpus, thus it could be easily extended to other languages and medical texts, such as electronic health records.
Age-associated myometrial dysfunction can prompt complications during pregnancy and labor, which is one of the factors contributing to the 7.8-fold increase in maternal mortality in women over 40. Using single-cell/single-nucleus RNA sequencing and spatial transcriptomics, we have constructed a cellular atlas of the aging myometrium from 186,120 cells across twenty perimenopausal and postmenopausal women. We identify 23 myometrial cell subpopulations, including contractile and venous capillary cells as well as immune-modulated fibroblasts. Myometrial aging leads to fewer contractile capillary cells, a reduced level of ion channel expression in smooth muscle cells, and impaired gene expression in endothelial, smooth muscle, fibroblast, perivascular, and immune cells. We observe altered myometrial cell-to-cell communication as an aging hallmark, which associated with the loss of 25 signaling pathways, including those related to angiogenesis, tissue repair, contractility, immunity, and nervous system regulation. These insights may contribute to a better understanding of the complications faced by older individuals during pregnancy and labor.
Since its emergence in March 2020, the SARS-CoV-2 global pandemic has produced more than 116 million cases and 2.5 million deaths worldwide. Despite the enormous efforts carried out by the scientific community, no effective treatments have been developed to date. We applied a novel computational pipeline aimed to accelerate the process of identifying drug repurposing candidates which allows us to compare three-dimensional protein structures. Its use in conjunction with two in silico validation strategies (molecular docking and transcriptomic analyses) allowed us to identify a set of potential drug repurposing candidates targeting three viral proteins (3CL viral protease, NSP15 endoribonuclease, and NSP12 RNA-dependent RNA polymerase), which included rutin, dexamethasone, and vemurafenib. This is the first time that a topological data analysis (TDA)-based strategy has been used to compare a massive number of protein structures with the final objective of performing drug repurposing to treat SARS-CoV-2 infection.