Computational Approaches for Predicting Preterm Birth and Newborn Outcomes.

Preterm birth (PTB) and its associated morbidities are a leading cause of infant mortality and morbidity. Accurate predictive models and a better biological understanding of PTB-associated morbidities are critical in reducing their adverse effects. Increasing availability of multimodal high-dimensional data sets with concurrent advances in artificial intelligence (AI) have created a rich opportunity to gain novel insights into PTB, a clinically complex and multifactorial disease. Here, the authors review the use of AI to analyze 3 modes of data: electronic health records, biological omics, and social determinants of health metrics.

Comprehensive overview of the anesthesiology research landscape: A machine Learning Analysis of 737 NIH-funded anesthesiology primary Investigator's publication trends.

Background: Anesthesiology plays a crucial role in perioperative care, critical care, and pain management, impacting patient experiences and clinical outcomes. However, our understanding of the anesthesiology research landscape is limited. Accordingly, we initiated a data-driven analysis through topic modeling to uncover research trends, enabling informed decision-making and fostering progress within the field. Methods: The easyPubMed R package was used to collect 32,300 PubMed abstracts spanning from 2000 to 2022. These abstracts were authored by 737 Anesthesiology Principal Investigators (PIs) who were recipients of National Institute of Health (NIH) funding from 2010 to 2022. Abstracts were preprocessed, vectorized, and analyzed with the state-of-the-art BERTopic algorithm to identify pillar topics and trending subtopics within anesthesiology research. Temporal trends were assessed using the Mann-Kendall test. Results: The publishing journals with most abstracts in this dataset were Anesthesia & Analgesia 1133, Anesthesiology 992, and Pain 671. Eight pillar topics were identified and categorized as basic or clinical sciences based on a hierarchical clustering analysis. Amongst the pillar topics, "Cells & Proteomics" had both the highest annual and total number of abstracts. Interestingly, there was an overall upward trend for all topics spanning the years 2000-2022. However, when focusing on the period from 2015 to 2022, topics "Cells & Proteomics" and "Pulmonology" exhibit a downward trajectory. Additionally, various subtopics were identified, with notable increasing trends in "Aneurysms", "Covid 19 Pandemic", and "Artificial intelligence & Machine Learning". Conclusion: Our work offers a comprehensive analysis of the anesthesiology research landscape by providing insights into pillar topics, and trending subtopics. These findings contribute to a better understanding of anesthesiology research and can guide future directions.

Transitional dendritic cells are distinct from conventional DC2 precursors and mediate proinflammatory antiviral responses.

High-dimensional approaches have revealed heterogeneity amongst dendritic cells (DCs), including a population of transitional DCs (tDCs) in mice and humans. However, the origin and relationship of tDCs to other DC subsets has been unclear. Here we show that tDCs are distinct from other well-characterized DCs and conventional DC precursors (pre-cDCs). We demonstrate that tDCs originate from bone marrow progenitors shared with plasmacytoid DCs (pDCs). In the periphery, tDCs contribute to the pool of ESAM+ type 2 DCs (DC2s), and these DC2s have pDC-related developmental features. Different from pre-cDCs, tDCs have less turnover, capture antigen, respond to stimuli and activate antigen-specific naïve T cells, all characteristics of differentiated DCs. Different from pDCs, viral sensing by tDCs results in IL-1ß secretion and fatal immune pathology in a murine coronavirus model. Our findings suggest that tDCs are a distinct pDC-related subset with a DC2 differentiation potential and unique proinflammatory function during viral infections.

Rapid recruitment and IFN-I-mediated activation of monocytes dictate focal radiotherapy efficacy.

The recruitment of monocytes and their differentiation into immunosuppressive cells is associated with the low efficacy of preclinical nonconformal radiotherapy (RT) for tumors. However, nonconformal RT (non-CRT) does not mimic clinical practice, and little is known about the role of monocytes after RT modes used in patients, such as conformal RT (CRT). Here, we investigated the acute immune response induced by after CRT. Contrary to non-CRT approaches, we found that CRT induces a rapid and robust recruitment of monocytes to the tumor that minimally differentiate into tumor-associated macrophages or dendritic cells but instead up-regulate major histocompatibility complex II and costimulatory molecules. We found that these large numbers of infiltrating monocytes are responsible for activating effector polyfunctional CD8+ tumor-infiltrating lymphocytes that reduce tumor burden. Mechanistically, we show that monocyte-derived type I interferon is pivotal in promoting monocyte accumulation and immunostimulatory function in a positive feedback loop. We also demonstrate that monocyte accumulation in the tumor microenvironment is hindered when RT inadvertently affects healthy tissues, as occurs in non-CRT. Our results unravel the immunostimulatory function of monocytes during clinically relevant modes of RT and demonstrate that limiting the exposure of healthy tissues to radiation has a positive therapeutic effect on the overall antitumor immune response.

Full sequence of mutant huntingtin 3'-untranslated region and modulation of its gene regulatory activity by endogenous microRNA.

Huntington's disease (HD) is caused by an expanded CAG trinucleotide repeat in the first exon of the huntingtin gene (HTT). Since the entire course of the disease starts from this dominant gain-of-function mutation, lowering total or mutant huntingtin mRNA/protein has emerged as an appealing therapeutic strategy. We reasoned that endogenous mechanisms underlying HTT gene regulation may inform strategies to target the source of the disease. As part of our investigation to understand how the expression of HTT is controlled, we performed (1) complete sequencing analysis for mutant HTT 3'-UTR and (2) unbiased screening assays to identify naturally-occurring miRNAs that could lower the HTT mRNA levels. By sequencing HD families inheriting the major European mutant haplotype, we determined the full sequence of HTT 3'-UTRs of the most frequent mutant (i.e., hap.01) and normal (i.e., hap.08) haplotypes, revealing 5 sites with alternative alleles. In subsequent miRNA activity assays using the full-length hap.01 and hap.08 3'-UTR reporter vectors and follow-up validation experiments, hsa-miR-4324 and hsa-miR-4756-5p significantly reduced HTT 3'-UTR reporter activity and endogenous HTT protein levels. However, those miRNAs did not show strong haplotype-specific effects. Nevertheless, our data highlighting full sequences of HTT 3'-UTR haplotypes, effects of miRNAs on HTT levels, and potential interaction sites provide rationale and promising targets for total and mutant-specific HTT lowering intervention strategies using endogenous and artificial miRNAs, respectively.