Immunobiology of Acute Chorioamnionitis.

Acute chorioamnionitis is characterized by neutrophilic infiltration and inflammation at the maternal fetal interface. It is a relatively common complication of pregnancy and can have devastating consequences including preterm labor, maternal infections, fetal infection/inflammation, fetal lung, brain, and gastrointestinal tract injury. In this review, we will discuss current understanding of the pathogenesis, immunobiology, and mechanisms of this condition. Most commonly, acute chorioamnionitis is a result of ascending infection with relatively low-virulence organisms such as the Ureaplasma species. Furthermore, recent vaginal microbiome studies suggest that there is a link between vaginal dysbiosis, vaginal inflammation, and ascending infection. Although less common, microorganisms invading the maternal-fetal interface via hematogenous route (e.g., Zika virus, Cytomegalovirus, and Listeria) can cause placental villitis and severe fetal inflammation and injury. We will provide an overview of the knowledge gleaned from different animal models of acute chorioamnionitis and the role of different immune cells in different maternal-fetal compartments. Lastly, we will discuss how infectious agents can break the maternal tolerance of fetal allograft during pregnancy and highlight the novel future therapeutic approaches

Comparing the safety of COVID-19 vaccines: a geometrical approach

The prompt development of multiple vaccines for the immunization against the world-wide spread of the COVID-19 infection has raised the issue of comparison of their efficacy and of symptomatic effects on the population treated. The different trial reports, made available from the vaccine producers and from the regulatory authorities, analyze some selected systemic reactions reported from patients after the doses received, these are given in a graded scale. In this contribute we propose a geometric way to compare frequency distributions of categorical variables by introducing a distance measure from the best possible scenario in this repartition. The measure proposed is suitable for a direct comparison among the vaccines in terms of the severity of symptomatic reactions

Platinum sensitivity and DNA repair in a recently established panel of patient-derived ovarian carcinoma xenografts

A xenobank of patient-derived (PDX) ovarian tumor samples has been established consisting of tumors with different sensitivity to cisplatin (DDP), from very responsive to resistant. As the DNA repair pathway is an important driver in tumor response to DDP, we analyzed the mRNA expression of 20 genes involved in the nucleotide excision repair, fanconi anemia, homologous recombination, base excision repair, mismatch repair and translesion repair pathways and the methylation patterns of some of these genes. We also investigated the correlation with the response to platinum-based therapy. The mRNA levels of the selected genes were evaluated by Real Time-PCR (RT-PCR) with ad hoc validated primers and gene promoter methylation by pyrosequencing. All the DNA repair genes were variably expressed in all 42 PDX samples analyzed, with no particular histotype-specific pattern of expression. In high-grade serous/endometrioid PDXs, the CDK12 mRNA expression levels positively correlated with the expression of TP53BP1, PALB2, XPF and POLB. High-grade serous/endometrioid PDXs with TP53 mutations had significantly higher levels of POLQ, FANCD2, RAD51 and POLB than high-grade TP53 wild type PDXs. The mRNA levels of CDK12, PALB2 and XPF inversely associated with the in vivo DDP antitumor activity; higher CDK12 mRNA levels were associated with a higher recurrence rate in ovarian patients with low residual tumor. These data support the important role of CDK12 in the response to a platinum based therapy in ovarian patients

Cell-Cycle Inhibition by Helicobacter pylori L-Asparaginase

Helicobacter pylori (H. pylori) is a major human pathogen causing chronic gastritis, peptic ulcer, gastric cancer, and mucosa-associated lymphoid tissue lymphoma. One of the mechanisms whereby it induces damage depends on its interference with proliferation of host tissues. We here describe the discovery of a novel bacterial factor able to inhibit the cell-cycle of exposed cells, both of gastric and non-gastric origin. An integrated approach was adopted to isolate and characterise the molecule from the bacterial culture filtrate produced in a protein-free medium: size-exclusion chromatography, non-reducing gel electrophoresis, mass spectrometry, mutant analysis, recombinant protein expression and enzymatic assays. L-asparaginase was identified as the factor responsible for cell-cycle inhibition of fibroblasts and gastric cell lines. Its effect on cell-cycle was confirmed by inhibitors, a knockout strain and the action of recombinant L-asparaginase on cell lines. Interference with cell-cycle in vitro depended on cell genotype and was related to the expression levels of the concurrent enzyme asparagine synthetase. Bacterial subcellular distribution of L-asparaginase was also analysed along with its immunogenicity. H. pylori L-asparaginase is a novel antigen that functions as a cell-cycle inhibitor of fibroblasts and gastric cell lines. We give evidence supporting a role in the pathogenesis of H. pylori-related diseases and discuss its potential diagnostic application

KG-COVID-19: A Framework to Produce Customized Knowledge Graphs for COVID-19 Response.

Integrated, up-to-date data about SARS-CoV-2 and COVID-19 is crucial for the ongoing response to the COVID-19 pandemic by the biomedical research community. While rich biological knowledge exists for SARS-CoV-2 and related viruses (SARS-CoV, MERS-CoV), integrating this knowledge is difficult and time-consuming, since much of it is in siloed databases or in textual format. Furthermore, the data required by the research community vary drastically for different tasks; the optimal data for a machine learning task, for example, is much different from the data used to populate a browsable user interface for clinicians. To address these challenges, we created KG-COVID-19, a flexible framework that ingests and integrates heterogeneous biomedical data to produce knowledge graphs (KGs), and applied it to create a KG for COVID-19 response. This KG framework also can be applied to other problems in which siloed biomedical data must be quickly integrated for different research applications, including future pandemics

KG-Hub-building and exchanging biological knowledge graphs.

MOTIVATION: Knowledge graphs (KGs) are a powerful approach for integrating heterogeneous data and making inferences in biology and many other domains, but a coherent solution for constructing, exchanging, and facilitating the downstream use of KGs is lacking. RESULTS: Here we present KG-Hub, a platform that enables standardized construction, exchange, and reuse of KGs. Features include a simple, modular extract-transform-load pattern for producing graphs compliant with Biolink Model (a high-level data model for standardizing biological data), easy integration of any OBO (Open Biological and Biomedical Ontologies) ontology, cached downloads of upstream data sources, versioned and automatically updated builds with stable URLs, web-browsable storage of KG artifacts on cloud infrastructure, and easy reuse of transformed subgraphs across projects. Current KG-Hub projects span use cases including COVID-19 research, drug repurposing, microbial-environmental interactions, and rare disease research. KG-Hub is equipped with tooling to easily analyze and manipulate KGs. KG-Hub is also tightly integrated with graph machine learning (ML) tools which allow automated graph ML, including node embeddings and training of models for link prediction and node classification. AVAILABILITY AND IMPLEMENTATION: https://kghub.org

IL-17 signaling accelerates the progression of nonalcoholic fatty liver disease in mice

Inflammation plays a central pathogenic role in the pernicious metabolic and end-organ sequelae of obesity. Among these sequelae, nonalcoholic fatty liver disease (NAFLD) has become the most common chronic liver disease in the developed world. The twinned observations that obesity is associated with increased activation of the interleukin (IL)-17 axis and that this axis can regulate liver damage in diverse contexts prompted us to address the role of IL-17RA signaling in the progression of NAFLD. We further examined whether microbe-driven IL-17A regulated NAFLD development and progression. We show here that IL-17RA−/− mice respond to high-fat diet stress with significantly greater weight gain, visceral adiposity, and hepatic steatosis than wild-type controls. However, obesity-driven lipid accumulation was uncoupled from its end-organ consequences in IL-17RA−/− mice, which exhibited decreased steatohepatitis, nicotinamide adenine dinucleotide phosphate (NADPH)-oxidase enzyme expression, and hepatocellular damage. Neutralization of IL-17A significantly reduced obesity-driven hepatocellular damage in wild-type mice. Further, colonization of mice with segmented filamentous bacteria (SFB), a commensal that induces IL-17A production, exacerbated obesity-induced hepatocellular damage. In contrast, SFB depletion protected from obesity-induced hepatocellular damage. Conclusion: These data indicate that obesity-driven activation of the IL-17 axis is central to the development and progression of NAFLD to steatohepatitis and identify the IL-17 pathway as a novel therapeutic target in this condition. (Hepatology 2014;59:1830–1839

Human Herpesvirus-8 Infection Leads to Expansion of the Preimmune/Natural Effector B Cell Compartment

BACKGROUND: Human herpesvirus-8 (HHV-8) is the etiological agent of Kaposi's sarcoma (KS) and of some lymphoproliferative disorders of B cells. Most malignancies develop after long-lasting viral dormancy, and a preventing role for both humoral and cellular immune control is suggested by the high frequency of these pathologies in immunosuppressed patients. B cells, macrophages and dendritic cells of peripheral lymphoid organs and blood represent the major reservoir of HHV-8. Due to the dual role of B cells in HHV-8 infection, both as virus reservoir and as agents of humoral immune control, we analyzed the subset distribution and the functional state of peripheral blood B cells in HHV-8-infected individuals with and without cKS. METHODOLOGY/PRINCIPAL FINDINGS: Circulating B cells and their subsets were analyzed by 6-color flow cytometry in the following groups: 1- patients HHV-8 positive with classic KS (cKS) (n = 47); 2- subjects HHV-8 positive and cKS negative (HSP) (n = 10); 3- healthy controls, HHV-8 negative and cKS negative (HC) (n = 43). The number of B cells belonging to the preimmune/natural effector compartment, including transitional, pre-naïve, naïve and MZ-like subsets, was significantly higher among HHV-8 positive subjects, with or without cKS, while was comparable to healthy controls in the antigen-experienced T-cell dependent compartment. The increased number of preimmune/natural effector B cells was associated with increased resistance to spontaneous apoptosis, while it did not correlate with HHV-8 viral load. CONCLUSIONS/SIGNIFICANCE: Our results indicate that long-lasting HHV-8 infection promotes an imbalance in peripheral B cell subsets, perturbing the equilibrium between earlier and later steps of maturation and activation processes. This observation may broaden our understanding of the complex interplay between viral and immune factors leading HHV-8-infected individuals to develop HHV-8-associated malignancies

The Monarch Initiative in 2024: an analytic platform integrating phenotypes, genes and diseases across species.

Bridging the gap between genetic variations, environmental determinants, and phenotypic outcomes is critical for supporting clinical diagnosis and understanding mechanisms of diseases. It requires integrating open data at a global scale. The Monarch Initiative advances these goals by developing open ontologies, semantic data models, and knowledge graphs for translational research. The Monarch App is an integrated platform combining data about genes, phenotypes, and diseases across species. Monarch\u27s APIs enable access to carefully curated datasets and advanced analysis tools that support the understanding and diagnosis of disease for diverse applications such as variant prioritization, deep phenotyping, and patient profile-matching. We have migrated our system into a scalable, cloud-based infrastructure; simplified Monarch\u27s data ingestion and knowledge graph integration systems; enhanced data mapping and integration standards; and developed a new user interface with novel search and graph navigation features. Furthermore, we advanced Monarch\u27s analytic tools by developing a customized plugin for OpenAI\u27s ChatGPT to increase the reliability of its responses about phenotypic data, allowing us to interrogate the knowledge in the Monarch graph using state-of-the-art Large Language Models. The resources of the Monarch Initiative can be found at monarchinitiative.org and its corresponding code repository at github.com/monarch-initiative/monarch-app