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Understanding the role of stress in pregnancy and its consequences is important, particularly given documented associations between maternal stress and preterm birth and other pathological outcomes. Physical and psychological stressors can elicit the same biological responses, known as biological strain. Chronic stressors, like poverty and racism (race-based discriminatory treatment), may create a legacy or trajectory of biological strain that no amount of coping can relieve in the absence of larger-scale socio-behavioral or societal changes. An integrative approach that takes into consideration simultaneously social and biological determinants of stress may provide the best insights into the risk of preterm birth. The most successful computational approaches and the most predictive machine-learning models are likely to be those that combine information about the stressors and the biological strain (for example, as measured by different omics) experienced during pregnancy. [ABSTRACT FROM AUTHOR]

Technologies for single‐cell profiling of the immune system have enabled researchers to extract rich interconnected networks of cellular abundance, phenotypical and functional cellular parameters. These studies can power machine learning approaches to understand the role of the immune system in various diseases. However, the performance of these approaches and the generalizability of the findings have been hindered by limited cohort sizes in translational studies, partially due to logistical demands and costs associated with longitudinal data collection in sufficiently large patient cohorts. An evolving challenge is the requirement for ever‐increasing cohort sizes as the dimensionality of datasets grows. We propose a deep learning model derived from a novel pipeline of optimal temporal cell matching and overcomplete autoencoders that uses data from a small subset of patients to learn to forecast an entire patient's immune response in a high dimensional space from one timepoint to another. In our analysis of 1.08 million cells from patients pre‐ and post‐surgical intervention, we demonstrate that the generated patient‐specific data are qualitatively and quantitatively similar to real patient data by demonstrating fidelity, diversity, and usefulness. [ABSTRACT FROM AUTHOR]

Objectives The aim of the study was to: (1) Identify (early in pregnancy) psychosocial and stress-related factors that predict risk of spontaneous preterm birth (PTB, gestational age <37 weeks); (2) Investigate whether "protective" factors (e.g., happiness/social support) decrease risk; (3) Use the Dhabhar Quick-Assessment Questionnaire for Stress and Psychosocial Factors (DQAQ-SPF) to rapidly quantify harmful or protective factors that predict increased or decreased risk respectively, of PTB. Study Design This is a prospective cohort study. Relative risk (RR) analyses investigated association between individual factors and PTB. Machine learning-based interdependency analysis (IDPA) identified factor clusters, strength, and direction of association with PTB. A nonlinear model based on support vector machines was built for predicting PTB and identifying factors that most strongly predicted PTB. Results Higher levels of deleterious factors were associated with increased RR for PTB: General anxiety (RR = 8.9; 95% confidence interval [CI] = 2.0,39.6), pain (RR = 5.7; CI = 1.7,17.0); tiredness/fatigue (RR = 3.7; CI = 1.09,13.5); perceived risk of birth complications (RR = 4; CI = 1.6,10.01); self-rated health current (RR = 2.6; CI = 1.0,6.7) and previous 3 years (RR = 2.9; CI = 1.1,7.7); and divorce (RR = 2.9; CI = 1.1,7.8). Lower levels of protective factors were also associated with increased RR for PTB: low happiness (RR = 9.1; CI = 1.25,71.5); low support from parents/siblings (RR = 3.5; CI = 0.9,12.9), and father-of-baby (RR = 3; CI = 1.1,9.9). These factors were also components of the clusters identified by the IDPA: perceived risk of birth complications (p < 0.05 after FDR correction), and general anxiety, happiness, tiredness/fatigue, self-rated health, social support, pain, and sleep (p < 0.05 without FDR correction). Supervised analysis of all factors, subject to cross-validation, produced a model highly predictive of PTB (AUROC or area under the receiver operating characteristic = 0.73). Model reduction through forward selection revealed that even a small set of factors (including those identified by RR and IDPA) predicted PTB. Conclusion These findings represent an important step toward identifying key factors, which can be assessed rapidly before/after conception, to predict risk of PTB, and perhaps other adverse pregnancy outcomes. Quantifying these factors, before, or early in pregnancy, could identify women at risk of delivering preterm, pinpoint mechanisms/targets for intervention, and facilitate the development of interventions to prevent PTB. Key Points Newly designed questionnaire used for rapid quantification of stress and psychosocial factors early during pregnancy. Deleterious factors predict increased preterm birth (PTB) risk. Protective factors predict decreased PTB risk. [ABSTRACT FROM AUTHOR]

Background: Among chronic opioid users, the association between decreasing or increasing preoperative opioid utilization and postoperative outcomes is unknown. The authors hypothesized that decreasing utilization would be associated with improved outcomes and increasing utilization with worsened outcomes.Methods: Using commercial insurance claims, the authors identified 57,019 chronic opioid users (10 or more prescriptions or 120 or more days supplied during the preoperative year), age 18 to 89 yr, undergoing one of 10 surgeries between 2004 and 2018. Patients with a 20% or greater decrease or increase in opioid utilization between preoperative days 7 to 90 and 91 to 365 were compared to patients with less than 20% change (stable utilization). The primary outcome was opioid utilization during postoperative days 91 to 365. Secondary outcomes included alternative measures of postoperative opioid utilization (filling a minimum number of prescriptions during this period), postoperative adverse events, and healthcare utilization.Results: The average age was 63 ± 13 yr, with 38,045 (66.7%) female patients. Preoperative opioid utilization was decreasing for 12,347 (21.7%) patients, increasing for 21,330 (37.4%) patients, and stable for 23,342 (40.9%) patients. Patients with decreasing utilization were slightly less likely to fill an opioid prescription during postoperative days 91 to 365 compared to stable patients (89.2% vs. 96.4%; odds ratio, 0.323; 95% CI, 0.296 to 0.352; P < 0.001), though the average daily doses were similar among patients who continued to utilize opioids during this timeframe (46.7 vs. 46.5 morphine milligram equivalents; difference, 0.2; 95% CI, -0.8 to 1.2; P = 0.684). Of patients with increasing utilization, 93.6% filled opioid prescriptions during this period (odds ratio, 0.57; 95% CI, 0.52 to 0.62; P < 0.001), with slightly lower average daily doses (44.3 morphine milligram equivalents; difference, -2.2; 95% CI, -3.1 to -1.3; P < 0.001). Except for alternative measures of persistent postoperative opioid utilization, there were no clinically significant differences for the secondary outcomes.Conclusions: Changes in preoperative opioid utilization were not associated with clinically significant differences for several postoperative outcomes including postoperative opioid utilization.Editor’s Perspective: [ABSTRACT FROM AUTHOR]

Approximately 1 in 4 pregnant women in the United States undergo labor induction. The onset and establishment of labor, particularly induced labor, is a complex and dynamic process influenced by multiple endocrine, inflammatory, and mechanical factors as well as obstetric and pharmacological interventions. The duration from labor induction to the onset of active labor remains unpredictable. Moreover, prolonged labor is associated with severe complications for the mother and her offspring, most importantly chorioamnionitis, uterine atony, and postpartum hemorrhage. While maternal immune system adaptations that are critical for the maintenance of a healthy pregnancy have been previously characterized, the role of the immune system during the establishment of labor is poorly understood. Understanding maternal immune adaptations during labor initiation can have important ramifications for predicting successful labor induction and labor complications in both induced and spontaneous types of labor. The aim of this study was to characterize labor-associated maternal immune system dynamics from labor induction to the start of active labor. Serial blood samples from fifteen participants were collected immediately prior to labor induction (baseline) and during the latent phase until the start of active labor. Using high-dimensional mass cytometry, a total of 1,059 single-cell immune features were extracted from each sample. A multivariate machine-learning method was employed to characterize the dynamic changes of the maternal immune system after labor induction until the establishment of active labor. A cross-validated linear sparse regression model (least absolute shrinkage and selection operator, LASSO) predicted the minutes since induction of labor with high accuracy (R = 0.86, p = 6.7e-15, RMSE = 277 min). Immune features most informative for the model included STAT5 signaling in central memory CD8+ T cells and pro-inflammatory STAT3 signaling responses across multiple adaptive and innate immune cell subsets. Our study reports a peripheral immune signature of labor induction, and provides important insights into biological mechanisms that may ultimately predict labor induction success as well as complications, thereby facilitating clinical decision-making to improve maternal and fetal well-being. [ABSTRACT FROM AUTHOR]

Although most causes of death and morbidity in premature infants are related to immune maladaptation, the premature immune system remains poorly understood. We provide a comprehensive single-cell depiction of the neonatal immune system at birth across the spectrum of viable gestational age (GA), ranging from 25 weeks to term. A mass cytometry immunoassay interrogated all major immune cell subsets, including signaling activity and responsiveness to stimulation. An elastic net model described the relationship between GA and immunome (R=0.85, p=8.75e-14), and unsupervised clustering highlighted previously unrecognized GA-dependent immune dynamics, including decreasing basal MAP-kinase/NFκB signaling in antigen presenting cells; increasing responsiveness of cytotoxic lymphocytes to interferon-α; and decreasing frequency of regulatory and invariant T cells, including NKT-like cells and CD8+CD161+ T cells. Knowledge gained from the analysis of the neonatal immune landscape across GA provides a mechanistic framework to understand the unique susceptibility of preterm infants to both hyper-inflammatory diseases and infections. [ABSTRACT FROM AUTHOR]

Abstract Background Two main classes of peripheral sensory neurons contribute to thermal pain sensitivity: the unmyelinated C fibers and thinly myelinated Aδ fibers. These two fiber types may differentially underlie different clinical pain states and distinctions in the efficacy of analgesic treatments. Methods of differentially testing C and Aδ thermal pain are widely used in animal experimentation, but these methods are not optimal for human volunteer and patient use. Thus, this project aimed to provide psychophysical and electrophysiological evidence that whether different protocols of infrared diode laser stimulation, which allows for direct activation of nociceptive terminals deep in the skin, could differentially activate Aδ or C fiber thermonociceptors in volunteers. Results Short (60 ms), high intensity laser pulses (SP) evoked monomodal "pricking" pain which was not enhanced by topical capsaicin, whereas longer, lower power pulses (LP) evoked monomodal "burning" pain which was enhanced by topical capsaicin. SP also produced cortical evoked EEG potentials consistent with Aδ mediation, the amplitude of which was directly correlated with pain intensity but was not affected by topical capsaicin. LP also produced a distinct evoked potential pattern the amplitude of which was also correlated with pain intensity, which was enhanced by topical capsaicin, and the latency of which could be used to estimate the conduction velocity of the mediating nociceptive fibers. Conclusions Psychophysical and electrophysiological data were consistent with the ability of short high intensity infrared laser pulses to selectively produce Aδ mediated pain and of longer pulses to selectively produce C fiber mediated thermal pain. Thus, the use of these or similar protocols may be useful in developing and testing novel therapeutics based on the differential molecular mechanisms underlying activation of the two fiber types (e.g., TRPV1, TRPV2, etc). In addition, these protocol may be useful in determining the fiber mediation of different clinical pain types which may, in turn be useful in treatment choice.

Abstract Background - The chronic use of opioids prior to surgery leads to lowered pain thresholds and exaggerated pain levels after these procedures. Several mechanisms have been proposed to explain this heightened sensitivity commonly termed opioid-induced hyperalgesia (OIH). Most of these proposed mechanisms involve plastic events in the central or peripheral nervous systems. Alterations in the abundance of peripheral mediators of nociception have not previously been explored. Results - In these experiments mice were treated with saline (control) or ascending daily doses of morphine to generate a state of OIH followed by hind paw incision. In other experiments morphine treatment was initiated at the time of incision. Both mechanical allodynia and peri-incisional skin cytokine levels were measured. Myeloperoxidase (MPO) assays were used to determine neutrophil activity near the wounds. The cytokine production inhibitor pentoxifylline was used to determine the functional significance of the excess cytokines in previously morphine treated animals. Mice treated chronically treated with morphine prior to incision were found to have enhanced skin levels of IL-1β, IL-6, G-CSF, KC and TNFα after incision at one or more time points compared to saline pretreated controls. The time courses of individual cytokines followed different patterns. There was no discernable effect of chronic morphine treatment on wound area neutrophil infiltration. Pentoxifylline reduced cytokine levels and reversed the excess mechanical sensitization caused by chronic morphine administration prior to incision. Morphine treatment initiated at the time of incision did not lead to a generalized enhancement of cytokine production or nociceptive sensitization in excess of the levels observed after incision alone. Conclusion - The enhanced level of nociceptive sensitization seen after incision in animals chronically exposed to morphine is associated with elevated levels of several cytokines previously reported to be relevant to this incisional pain model. The cytokines may be functional in supporting nociceptive sensitization because pentoxifylline reverses both peri-incisional skin cytokine levels and OIH. Opioid administration beginning at the time of incision does not seem to have the same cytokine enhancing effect. Approaches to postoperative pain control involving a reduction of cytokines may be an effective way to control excessive pain in patients chronically using opioids prior to surgical procedures.

Abstract Background Inflammation and nociceptive sensitization are hallmarks of tissue surrounding surgical incisions. Recent studies demonstrate that several cytokines may participate in the enhancement of nociception near these wounds. Since opioids like morphine interact with neutrophils and other immunocytes, it is possible that morphine exerts some of its antinociceptive action after surgical incision by altering the vigor of the inflammatory response. On the other hand, keratinocytes also express opioid receptors and have the capacity to produce cytokines after injury. Our studies were directed towards determining if opioids alter cytokine production near incisions and to identify cell populations responsible for producing these cytokines. Results A murine incisional model was used to measure the effects of acute morphine administration (0.1–10 mg/kg) on nociceptive thresholds, neutrophil infiltration and cytokine production in hind paw skin 30 minutes and 2 hours after incision. Incised hind paws displayed profound allodynia which was reduced by morphine (0.1–10 mg/kg) in the 2 hours following incision. Skin samples harvested from these mice showed enhanced levels of 5 cytokines: IL-1β, IL-6, tumor necrosis factor alpha (TNFα), granulocyte colony stimulating factor (G-CSF) and keratinocyte-derived cytokine (KC). Morphine reduced these incision-stimulated levels. Separate analyses measuring myeloperoxidase (MPO) and using immunohistochemistry demonstrated that morphine dose-dependently reduced the infiltration of neutrophils into the peri-incisional tissue. The dose of morphine required for reduction of cytokine accumulation, however, was below that required for inhibition of peri-incisional neutrophil infiltration. Additional immunohistochemical studies revealed wound edge keratinocytes as being an important source of cytokines in the acute phase after incision. Conclusion Acute morphine administration of doses as low as 0.1 mg/kg reduces peri-incisional cytokine expression. A reduction in neutrophil infiltration does not provide a complete explanation for this effect, and keratinocytes may be responsible for some incision area cytokine production. These studies suggest that morphine may alter the inflammatory milieu of incisional wounds, but these alterations do not likely contribute significantly to analgesia in the acute setting.