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Microglia, the resident immune cells of the brain, are highly ramified and motile and their morphology is strongly linked to their function. Microglia constantly monitor the brain parenchyma and are crucial for maintaining brain homeostasis and fine-tuning neuronal networks. Besides affecting neurons, anesthetics may have wide-ranging effects mediated by non-neuronal cells and in particular microglia. We thus examined the effect of two commonly used anesthetic agents, ketamine/xylazine and barbiturates, on microglial motility and morphology. A combination of two-photon in vivo imaging and electroencephalography (EEG) recordings in unanesthetized and anesthetized mice as well as automated analysis of ex vivo sections were used to assess morphology and dynamics of microglia. We found that administration of ketamine/xylazine and pentobarbital anesthesia resulted in quite distinct EEG profiles. Both anesthetics reduced microglial motility, but only ketamine/xylazine administration led to reduction of microglial complexity in vivo. The change of cellular dynamics in vivo was associated with a region-dependent reduction of several features of microglial cells ex vivo, such as the complexity index and the ramification length, whereas thiopental altered the size of the cytoplasm. Our results show that anesthetics have considerable effects on neuronal activity and microglial morphodynamics and that barbiturates may be a preferred anesthetic agent for the study of microglial morphology. These findings will undoubtedly raise compelling questions about the functional relevance of anesthetics on microglial cells in neuronal physiology and anesthesia-induced neurotoxicity.

Regional analgesia is worth performing in the multimodal postoperative management of hip fracture (HF) because it reduces hospital morbidity and mortality. The aim of this study is to compare the efficacy and side effects of the recently described \"Pericapsular Nerve Group (PENG) Block\" with those of the femoral block, which is considered the standard of care for postoperative pain control after femoral neck fracture. We conducted a comparative observational study at a university hospital (Saint Antoine Hospital, Sorbonne University, Paris, France), where the PENG block was introduced in August 2019. We include all patients from June to October 2019, who were coming for femoral neck fractures and who had an analgesic femoral block or PENG block before their surgery. The primary outcome was the comparison of cumulative postoperative morphine consumption 48 hours after surgery. Demographics, medical charts, and perioperative data of 42 patients were reviewed: 21 patients before (Femoral group) and 21 patients after the introduction of PENG block (PENG group) in clinical practice. Thirteen total hip arthroplasties (THA) and eight hemi arthroplasties (HA) were included in each group. Demographics were also comparable. The median, postoperative, morphine equivalent consumption at 48 hours was 10 [0-20] mg and 20 [0-50] mg in Femoral and PENG groups respectively (p = 0.458). No statistically significant differences were found in postoperative pain intensity, time to ambulation, incidence of morphine-related side effects, or length of hospital stay. The postoperative muscle strength of the quadriceps was greater in the PENG group than in the Femoral group (5/5 vs. 2/5, p = 0.001). In the management of hip fractures, PENG block is not associated in our study with a significant change in postoperative morphine consumption, compared to femoral block. However, it does significantly improve the immediate mobility of the operated limb, making it appropriate for inclusion in enhanced recovery programs after surgery.

Preeclampsia is one of the most severe pregnancy complications and a leading cause of maternal death. However, early diagnosis of preeclampsia remains a clinical challenge. Alterations in the normal immune adaptations necessary for the maintenance of a healthy pregnancy are central features of preeclampsia. However, prior analyses primarily focused on the static assessment of select immune cell subsets have provided limited information for the prediction of preeclampsia. Here, we used a high-dimensional mass cytometry immunoassay to characterize the dynamic changes of over 370 immune cell features (including cell distribution and functional responses) in maternal blood during healthy and preeclamptic pregnancies. We found a set of eight cell-specific immune features that accurately identified patients well before the clinical diagnosis of preeclampsia (median area under the curve (AUC) 0.91, interquartile range [0.82-0.92]). Several features recapitulated previously known immune dysfunctions in preeclampsia, such as elevated pro-inflammatory innate immune responses early in pregnancy and impaired regulatory T (Treg) cell signaling. The analysis revealed additional novel immune responses that were strongly associated with, and preceded the onset of preeclampsia, notably abnormal STAT5ab signaling dynamics in CD4 T cell subsets (AUC 0.92, = 8.0E-5). These results provide a global readout of the dynamics of the maternal immune system early in pregnancy and lay the groundwork for identifying clinically-relevant immune dysfunctions for the prediction and prevention of preeclampsia.

High-throughput single-cell analysis technologies produce an abundance of data that is critical for profiling the heterogeneity of cellular systems. We introduce VoPo (https://github.com/stanleyn/VoPo), a machine learning algorithm for predictive modeling and comprehensive visualization of the heterogeneity captured in large single-cell datasets. In three mass cytometry datasets, with the largest measuring hundreds of millions of cells over hundreds of samples, VoPo defines phenotypically and functionally homogeneous cell populations. VoPo further outperforms state-of-the-art machine learning algorithms in classification tasks, and identified immune-correlates of clinically-relevant parameters.

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.

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.

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.

When used as an add-on to regional anesthesia, virtual reality (VR) has been reported to provide anxiety-reducing benefits and sedation-sparing effects. However, its impact on patient satisfaction is still a matter of controversy. We investigated the feasibility and benefits of implementing intraoperative VR distraction in a French University Hospital (Hôpital Saint-Antoine, AP-HP). This monocentric observational before–after study included 100 patients who underwent ambulatory upper limb surgery under peripheral nerve block in January 2019, 50 before and 50 after implementation of an intraoperative VR distraction protocol. Primary outcome was patient self-rated satisfaction score evaluated right after surgery. Secondary outcomes included 2-month patient-reported satisfaction score, perioperative self-rated anxiety and intraoperative hemodynamic changes. Compared to former standard care, VR distraction was associated with significantly higher postoperative satisfaction scores (10 [IQR 9; 10] vs. 9 [8; 10], p < 0.001) still reported two months after surgery (10 [10;10] vs. 10 [8.5;10], p = 0.06). Patient median intraoperative anxiety score was lower in the VR group, compared to Standard Care group (0 [0; 2] vs. 3 [0.25; 7], p < 0.001), and occurrence of intraoperative hemodynamic changes was also lessened in the VR group (2% vs. 16%, 0R = 0.11[95% CI 0.002–0.87], p = 0.031). The present findings suggest that VR distraction program in the operating room could effectively improve patient satisfaction with anxiety-reduction and hemodynamic benefits.

Background Immunosuppression medication nonadherence has been associated with donor-specific antibodies and treatment-refractory rejection. Drug-level monitoring is a practical direct marker for nonadherence, as variations indicate erratic ingestion of medication. We previously reported that high variability in tacrolimus trough levels determined by the percent coefficient of variation (CV %) and standard deviation (SD) were associated with biopsy-proven rejection. We hypothesized that the CV % and SD in patients on a sirolimus/low-dose tacrolimus regimen may associate with self-reported medication nonadherence, rejection and donor-specific antibodies. Methods In this pilot feasibility study, we studied 37 biopsies in 23 pediatric renal transplant patients on both sirolimus and tacrolimus immunosuppression; CV %, SD, de novo donor-specific antibodies, rejection, and self-reported adherence were examined. Results A cut-off sirolimus CV % of 25 maximized the percentage of biopsies correctly classified as rejection (32 of 37, or 86 %, p  = 0.001). A cut-off tacrolimus CV % of 31 maximized the percentage of correctly classified biopsies (25 of 37, or 68 %, p  = 0.09). Among patients with both high sirolimus and tacrolimus CV %, 67 % developed de novo donor-specific antibodies ( p  = 0.002) with a DQ predominance and 71 % reported nonadherence ( p  = 0.05). Conclusions In pediatric renal transplantation, sirolimus and tacrolimus CV % is a potential tool for monitoring patients at risk for allograft rejection and donor-specific antibodies secondary to medication nonadherence.

NRC publication: Yes