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Preterm birth (PTB) is the leading cause of infant mortality globally. Research has focused on developing predictive models for PTB without prioritizing cost-effective interventions. Physical activity and sleep present unique opportunities for interventions in low- and middle-income populations (LMICs). However, objective measurement of physical activity and sleep remains challenging and self-reported metrics suffer from low-resolution and accuracy. In this study, we use physical activity data collected using a wearable device comprising over 181,944 h of data across N = 1083 patients. Using a new state-of-the art deep learning time-series classification architecture, we develop a 'clock' of healthy dynamics during pregnancy by using gestational age (GA) as a surrogate for progression of pregnancy. We also develop novel interpretability algorithms that integrate unsupervised clustering, model error analysis, feature attribution, and automated actigraphy analysis, allowing for model interpretation with respect to sleep, activity, and clinical variables. Our model performs significantly better than 7 other machine learning and AI methods for modeling the progression of pregnancy. We found that deviations from a normal 'clock' of physical activity and sleep changes during pregnancy are strongly associated with pregnancy outcomes. When our model underestimates GA, there are 0.52 fewer preterm births than expected (P = 1.01e − 67, permutation test) and when our model overestimates GA, there are 1.44 times (P = 2.82e − 39, permutation test) more preterm births than expected. Model error is negatively correlated with interdaily stability (P = 0.043, Spearman's), indicating that our model assigns a more advanced GA when an individual's daily rhythms are less precise. Supporting this, our model attributes higher importance to sleep periods in predicting higher-than-actual GA, relative to lower-than-actual GA (P = 1.01e − 21, Mann-Whitney U). Combining prediction and interpretability allows us to signal when activity behaviors alter the likelihood of preterm birth and advocates for the development of clinical decision support through passive monitoring and exercise habit and sleep recommendations, which can be easily implemented in LMICs. [ABSTRACT FROM AUTHOR]

Preterm birth is the leading cause of mortality in children under the age of five worldwide. Despite major efforts, we still lack the ability to accurately predict and effectively prevent preterm birth. While multiple factors contribute to preterm labor, dysregulations of immunological adaptations required for the maintenance of a healthy pregnancy is at its pathophysiological core. Consequently, a precise understanding of these chronologically paced immune adaptations and of the biological pacemakers that synchronize the pregnancy "immune clock" is a critical first step towards identifying deviations that are hallmarks of peterm birth. Here, we will review key elements of the fetal, placental, and maternal pacemakers that program the immune clock of pregnancy. We will then emphasize multiomic studies that enable a more integrated view of pregnancy-related immune adaptations. Such multiomic assessments can strengthen the biological plausibility of immunological findings and increase the power of biological signatures predictive of preterm birth [ABSTRACT FROM AUTHOR]

Glucocorticoids (GC) are a controversial yet commonly used intervention in the clinical management of acute inflammatory conditions, including sepsis or traumatic injury. In the context of major trauma such as surgery, concerns have been raised regarding adverse effects from GC, thereby necessitating a better understanding of how GCs modulate the immune response. Here we report the results of a randomized controlled trial (NCT02542592) in which we employ a high-dimensional mass cytometry approach to characterize innate and adaptive cell signaling dynamics after a major surgery (primary outcome) in patients treated with placebo or methylprednisolone (MP). A robust, unsupervised bootstrap clustering of immune cell subsets coupled with random forest analysis shows profound (AUC = 0.92, p-value = 3.16E-8) MP-induced alterations of immune cell signaling trajectories, particularly in the adaptive compartments. By contrast, key innate signaling responses previously associated with pain and functional recovery after surgery, including STAT3 and CREB phosphorylation, are not affected by MP. These results imply cell-specific and pathway-specific effects of GCs, and also prompt future studies to examine GCs' effects on clinical outcomes likely dependent on functional adaptive immune responses. Glucocorticoids (GC) are commonly used to suppress undesirable inflammatory responses. Here the authors show, using hi-dimensional flow cytometry data, that GC treatment following major surgeries alters adaptive immunity without significant modulation of innate immune responses or pain/functional impairment. [ABSTRACT FROM AUTHOR]

Ageing drives changes in neuronal and cognitive function, the decline of which is a major feature of many neurological disorders. The hippocampus, a brain region subserving roles of spatial and episodic memory and learning, is sensitive to the detrimental effects of ageing at morphological and molecular levels. With advancing age, synapses in various hippocampal subfields exhibit impaired long-term potentiation, an electrophysiological correlate of learning and memory. At the molecular level, immediate early genes are among the synaptic plasticity genes that are both induced by long-term potentiation and downregulated in the aged brain. In addition to revitalizing other aged tissues, exposure to factors in young blood counteracts age-related changes in these central nervous system parameters, although the identities of specific cognition-promoting factors or whether such activity exists in human plasma remains unknown. We hypothesized that plasma of an early developmental stage, namely umbilical cord plasma, provides a reservoir of such plasticity-promoting proteins. Here we show that human cord plasma treatment revitalizes the hippocampus and improves cognitive function in aged mice. Tissue inhibitor of metalloproteinases 2 (TIMP2), a blood-borne factor enriched in human cord plasma, young mouse plasma, and young mouse hippocampi, appears in the brain after systemic administration and increases synaptic plasticity and hippocampal-dependent cognition in aged mice. Depletion experiments in aged mice revealed TIMP2 to be necessary for the cognitive benefits conferred by cord plasma. We find that systemic pools of TIMP2 are necessary for spatial memory in young mice, while treatment of brain slices with TIMP2 antibody prevents long-term potentiation, arguing for previously unknown roles for TIMP2 in normal hippocampal function. Our findings reveal that human cord plasma contains plasticity-enhancing proteins of high translational value for targeting ageing- or disease-associated hippocampal dysfunction. [ABSTRACT FROM AUTHOR]

Arterial blood sampling is necessary when drugs such as the fast-acting opioid analgesic remifentanil exhibit relevant differences between arterial and venous blood concentrations. Arterial cannulation is generally considered to be clinically safe and has thus become a standard procedure in pharmacokinetic-pharmacodynamic assessments. However, rare cases of arterial occlusions have to be considered in risk-benefit assessments of arterial sampling in pharmacokinetic studies, especially when including healthy volunteers. In an actual case, arterial occlusion requiring surgical repair was caused by a factor V Leiden thrombophilia associated genetic variant F5 1691G>A (rs6025) and aggravated by a hypoplastic radial artery. Neither risk factor had been identified prior to enrolment by routine laboratory tests such as the prothrombin time (international normalized ratio), partial thromboplastin time and the clinical Allen's test of arterial function. Re-assessment of the necessity of arterial sampling showed that none of the potential alternatives, target concentrations of computerized infusions or venous concentrations during non-steady-state and steady-state conditions could provide the arterial concentrations. Relying on venous concentrations may result in erroneous pharmacodynamic parameters. Accurate pharmacokinetic-pharmacodynamic studies relying on precisely measured blood concentrations require serial sampling techniques during both steady-state and non-steady-state conditions. However, as illustrated by the presented case, incidents involving the generally safe procedure of arterial sampling are possible, although rare. To further minimize the risks, screening of subjects for prothrombotic risks and careful assessment of the suitability of the artery should be considered in pharmacokinetic studies requiring arterial cannulation. [ABSTRACT FROM AUTHOR]

Lamellar liposome technology has been used for several decades to produce sustained-release drug formulations for parenteral administration. Multivesicular liposomes are structurally distinct from lamellar liposomes and consist of an aggregation of hundreds of water-filled polyhedral compartments separated by bi-layered lipid septa. The unique architecture of multivesicular liposomes allows encapsulating drug with greater efficiency, provides robust structural stability and ensures reliable, steady and prolonged drug release.The favourable characteristics of multivesicular liposomes have resulted in many drug formulations exploiting this technology, which is proprietary and referred to as DepoFoam™. Currently, two formulations using multivesicular liposome technology are approved by the US FDA for clinical use, and many more formulations are at an experimental developmental stage. The first clinically available formulation contains the antineoplastic agent cytarabine (DepoCyt™) for its intrathecal injection in the treatment of malignant lymphomatous meningitis. Intrathecal injection of DepoCyt™ reliably results in the sustained release of cytarabine and produces cytotoxic concentrations in cerebrospinal fluid (CSF) that are maintained for at least 2 weeks. Early efficacy data suggest that DepoCyt™ is fairly well tolerated, and its use allows reduced dosing frequency from twice a week to once every other week and may improve the outcome compared with frequent intrathecal injections of unencapsulated cytarabine. The second available formulation contains morphine (DepoDur™) for its single epidural injection in the treatment of postoperative pain. While animal studies confirm that epidural injection of DepoDur™ results in the sustained release of morphine into CSF, the CSF pharmacokinetics have not been determined in humans. Clinical studies suggest that the use of DepoDur™ decreases the amount of systemically administered analgesics needed for adequate postoperative pain control. It may also provide superior pain control during the first 1–2 postoperative days compared with epidural administration of unencapsulated morphine or intravenous administration of an opioid. However, at this timepoint the overall clinical utility of DepoDur™ has yet to be defined and some safety concerns remain because of the unknown CSF pharmacokinetics of DepoDur™ in humans.The versatility of multivesicular liposome technology is reflected by the many agents including small inorganic and organic molecules and macromolecules including proteins that have successfully been encapsulated. Data concerning many experimental formulations containing antineoplastic, antibacterial and antiviral agents underscore the sustained, steady and reliable release of these compounds from multivesicular liposomes after injection by the intrathecal, subcutaneous, intramuscular, intraperitoneal and intraocular routes. Contingent on the specific formulation and manufacturing process, agents were released over a period of hours to weeks as reflected by a 2- to 400-fold increase in elimination half life. Published data further suggest that the encapsulation process preserves bioactivity of agents as delicate as proteins and supports the view that examined multivesicular liposomes were non-toxic at studied doses. The task ahead will be to examine whether the beneficial structural and pharmacokinetic properties of multivesicular liposome formulations will translate into improved clinical outcomes, either because of decreased drug toxicity or increased drug efficacy. [ABSTRACT FROM AUTHOR]

An amendment to this paper has been published and can be accessed via a link at the top of the paper. [ABSTRACT FROM AUTHOR]

Pain medication plays an important role in the treatment of acute and chronic pain conditions, but some drugs, opioids in particular, have been overprescribed or prescribed without adequate safeguards, leading to an alarming rise in medication-related overdose deaths. The NIH Helping to End Addiction Long-term (HEAL) Initiative is a trans-agency effort to provide scientific solutions to stem the opioid crisis. One component of the initiative is to support biomarker discovery and rigorous validation in collaboration with industry leaders to accelerate high-quality clinical research into neurotherapeutics and pain. The use of objective biomarkers and clinical trial end points throughout the drug discovery and development process is crucial to help define pathophysiological subsets of pain, evaluate target engagement of new drugs and predict the analgesic efficacy of new drugs. In 2018, the NIH-led Discovery and Validation of Biomarkers to Develop Non-Addictive Therapeutics for Pain workshop convened scientific leaders from academia, industry, government and patient advocacy groups to discuss progress, challenges, gaps and ideas to facilitate the development of biomarkers and end points for pain. The outcomes of this workshop are outlined in this Consensus Statement. [ABSTRACT FROM AUTHOR]

Advanced measurement and data storage technologies have enabled high-dimensional profiling of complex biological systems. For this, modern multiomics studies regularly produce datasets with hundreds of thousands of measurements per sample, enabling a new era of precision medicine. Correlation analysis is an important first step to gain deeper insights into the coordination and underlying processes of such complex systems. However, the construction of large correlation networks in modern high-dimensional datasets remains a major computational challenge owing to rapidly growing runtime and memory requirements. Here we address this challenge by introducing CorALS (Correlation Analysis of Large-scale (biological) Systems), an open-source framework for the construction and analysis of large-scale parametric as well as non-parametric correlation networks for high-dimensional biological data. It features off-the-shelf algorithms suitable for both personal and high-performance computers, enabling workflows and downstream analysis approaches. We illustrate the broad scope and potential of CorALS by exploring perspectives on complex biological processes in large-scale multiomics and single-cell studies., Competing Interests: Competing interests The authors declare no competing interests.

The dense network of interconnected cellular signalling responses that are quantifiable in peripheral immune cells provides a wealth of actionable immunological insights. Although high-throughput single-cell profiling techniques, including polychromatic flow and mass cytometry, have matured to a point that enables detailed immune profiling of patients in numerous clinical settings, the limited cohort size and high dimensionality of data increase the possibility of false-positive discoveries and model overfitting. We introduce a generalizable machine learning platform, the immunological Elastic-Net (iEN), which incorporates immunological knowledge directly into the predictive models. Importantly, the algorithm maintains the exploratory nature of the high-dimensional dataset, allowing for the inclusion of immune features with strong predictive capabilities even if not consistent with prior knowledge. In three independent studies our method demonstrates improved predictions for clinically relevant outcomes from mass cytometry data generated from whole blood, as well as a large simulated dataset. The iEN is available under an open-source licence., Competing Interests: Competing interests The authors declare no competing interests.