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Daily Anesthesiology Research Analysis

3 papers

Three papers stand out in anesthesiology today: a rigorous mechanistic study unveils a peripheral c‑Jun–Mrgprd–DS‑lncRNA–Ehmt2/G9a–Oprm1 axis driving morphine tolerance; a compact ECG-based machine learning model accurately predicts inadequate anesthesia depth (BIS >60) minutes in advance; and a cluster-randomized cross-over trial finds no pulmonary hemodynamic or RV functional advantage of vasopressin over norepinephrine during cardiac surgery.

Summary

Three papers stand out in anesthesiology today: a rigorous mechanistic study unveils a peripheral c‑Jun–Mrgprd–DS‑lncRNA–Ehmt2/G9a–Oprm1 axis driving morphine tolerance; a compact ECG-based machine learning model accurately predicts inadequate anesthesia depth (BIS >60) minutes in advance; and a cluster-randomized cross-over trial finds no pulmonary hemodynamic or RV functional advantage of vasopressin over norepinephrine during cardiac surgery.

Research Themes

  • Mechanisms of opioid tolerance and peripheral sensory neuron signaling
  • AI-enabled perioperative monitoring without EEG
  • Vasopressor selection in cardiac surgery hemodynamics

Selected Articles

1. Modulation of morphine tolerance by Mas-related G protein-coupled receptor D signalling in the mouse dorsal root ganglion.

84Level VCase-controlBritish journal of anaesthesia · 2025PMID: 41271469

Time-resolved transcriptomics and in vivo manipulations identified a peripheral c‑Jun–Mrgprd–DS‑lncRNA–Ehmt2/G9a–Oprm1 pathway that drives morphine tolerance by reprogramming DRG gene expression. Suppressing Mrgprd delayed tolerance and increased MOR, whereas overexpression accelerated tolerance; targeting DS‑lncRNA/Ehmt2 reversed these effects.

Impact: This is a first-of-its-kind mechanistic delineation of a peripheral pathway controlling opioid tolerance, shifting focus beyond central mechanisms and revealing druggable nodes.

Clinical Implications: Although preclinical, the identified c‑Jun–Mrgprd–DS‑lncRNA–Ehmt2/G9a–Oprm1 axis suggests new targets to mitigate opioid tolerance, potentially sustaining analgesic efficacy and reducing dose escalation and adverse effects.

Key Findings

  • Acute morphine reduced DRG Mrgprd expression by ~70% at 6–24 h, normalizing by day 4.
  • Mrgprd knockdown delayed, while AAV-Mrgprd overexpression accelerated, the development of morphine tolerance.
  • Morphine decreased c-Jun (~40%); c-Jun directly bound the Mrgprd promoter (ChIP-qPCR/luciferase).
  • Mrgprd knockdown increased Oprm1/MOR via DS-lncRNA upregulation and Ehmt2/G9a suppression; DS-lncRNA knockdown restored Ehmt2 and reinstated tolerance.

Methodological Strengths

  • Time-course RNA-seq integrated with in vivo gain/loss-of-function in DRG
  • Convergent molecular validation (ChIP-qPCR, luciferase) and behavioral readouts

Limitations

  • Preclinical mouse model; human translatability remains to be shown
  • Pharmacologic tools targeting this axis and off-target effects were not clinically evaluated

Future Directions: Validate the axis in human DRG/tissue, develop selective modulators (e.g., Mrgprd or DS‑lncRNA/Ehmt2), and test efficacy/safety in large-animal models and early-phase clinical trials.

2. Heart rate dynamics predict anaesthetic depth: a compact machine learning model.

74.5Level IIICohortBritish journal of anaesthesia · 2025PMID: 41271473

Using ECG-derived heart rate dynamics, gradient boosting models predicted BIS >60 with AUCs of 0.95 (0 min), 0.92 (5 min), 0.91 (10 min), and 0.90 (15 min). A compact 27-feature set preserved accuracy while improving computational speed by 110-fold, enabling practical, EEG-free depth-of-anesthesia alerts.

Impact: Demonstrates a low-footprint, generalizable approach to anticipate inadequate anesthesia using widely available ECG signals, potentially enhancing safety where EEG monitoring is unavailable.

Clinical Implications: Could be integrated into standard monitors to provide early warnings of light anesthesia, guide titration, and reduce awareness risk when EEG-based indices are unavailable.

Key Findings

  • Models achieved AUCs of 0.953 (0 min), 0.917 (5 min), 0.910 (10 min), and 0.903 (15 min) for predicting BIS >60.
  • A compact set of 27 features preserved high accuracy with a 110-fold improvement in computational speed.
  • Most informative features captured fractal characteristics of heart rate dynamics.

Methodological Strengths

  • Large multicenter-like cohort size (n=3338) with nested 10-fold cross-validation
  • Feature reduction yielding a clinically deployable, computationally efficient model

Limitations

  • Retrospective dataset; lack of external prospective validation
  • BIS >60 is a surrogate for inadequate anesthesia and may be influenced by artifacts

Future Directions: Prospective, multicenter validation; real-time integration into OR monitors; assessment across anesthetic agents, age groups, and comorbidities; evaluation of impact on awareness and hemodynamic events.

3. Cardiopulmonary Effects of Vasopressin Versus Norepinephrine in Cardiac Surgery Patients: a Single Cluster-Randomized Cross-over Trial.

72.5Level IRCTThe Journal of thoracic and cardiovascular surgery · 2025PMID: 41270859

In 153 cardiac surgery patients with intraoperative hypotension, vasopressin did not reduce pulmonary pressures (mPAP/MAP ratio) or improve right ventricular free wall strain compared with norepinephrine. Preoperative pulmonary hypertension did not modify treatment effects.

Impact: Provides a randomized, clinically relevant test of a common assumption favoring vasopressin for pulmonary hemodynamic advantages, yielding a clear negative result.

Clinical Implications: Vasopressor selection during cardiac surgery should not favor vasopressin over norepinephrine solely for expected pulmonary hemodynamic or RV functional benefits; decisions can be based on other factors (availability, cost, side-effect profile).

Key Findings

  • No significant difference in mPAP-to-MAP ratio between vasopressin and norepinephrine groups (effect 0.02; P=0.646).
  • No significant difference in right ventricular free wall strain (effect 3.45%; P=0.078).
  • Preoperative pulmonary hypertension did not interact with treatment effects on mPAP/MAP ratio or RV strain.

Methodological Strengths

  • Cluster-randomized multiple cross-over design in real-world cardiac surgery
  • Objective echocardiographic hemodynamic measures analyzed with appropriate interaction testing

Limitations

  • Single-center study with modest sample size may limit power for secondary endpoints
  • Blinding and protocolized dosing details are not specified; potential cluster-period effects

Future Directions: Multicenter RCTs powered for clinical outcomes (AKI, arrhythmias, ICU length of stay), dose–response evaluation, and subgroup analyses (bypass vs off-pump, pulmonary hypertension severity).