Impaired tissue oxygenation is the key pathomechanism in the development of organ dysfunction in shock; mitochondrial impairment can aggravate the condition. However, measuring tissue oxygenation directly and non-invasively still poses a clinical challenge. A novel device (COMET) allows the assessment of mitochondrial oxygen metabolism using the Protoporphyrin IX Triplet State Lifetime Technique (PpIX-TSLT). Critically ill patients, especially in sepsis, often exhibit oedema which may interfere with the COMET measurement. Furthermore, patients' physical activity level differs significantly before and during hospitalisation. Thus, the aim of this study was to identify the effects of physical activity and body composition on mitochondrial oxygen tension (mitoPO₂) and consumption (mitoVO₂) in healthy controls (N = 40). Furthermore, the study tested the repeatability of the COMET variables and identified covariates. Multiple COMET measurements were performed before (T₁, T₂), during and after (T₃, T₄) ergometry. Body composition was assessed by bioimpedance analysis. Physiological variables (blood pressure, heart rate, oxygen saturation) were recorded. In the analytical sample (n = 26), physical activity significantly decreased mitoVO₂; other COMET variables remained unchanged between T₂ and T₃. During ergometry, mitoPO₂ increased significantly. The distribution of body water significantly influenced mitoVO₂. In our setting, the method demonstrated moderate repeatability. Variables of fitness (heart rate recovery, phase angle and physical activity level), signal quality and duration of exposure to 5-aminolevulinic acid (obligatory for PpIX-TSLT) were identified as significant covariates of mitoVO₂. Mitochondrial oxygen delivery (mitoDO₂) was established as a new variable of COMET analysis. Results of this pilot study should be validated in future studies.

Functional reorganisation of the salience network (SN) has been proposed as one of the key pathomechanisms associated with central nociceptive processing in the chronic pain state. Being associated with an altered functional connectivity within the SN, these processes have been hypothesized to result from a loss of inhibitory function leading to node hyperexcitability and spontaneous pain. Combined resting-state BOLD functional magnetic resonance imaging (MRI) and ¹H-MR spectroscopy was applied to chronic back pain patients and healthy subjects to assess deviations from functional integrity (weighted closeness centrality [wCC], derived from resting-state functional MRI), oscillatory BOLD characteristics (spectral power), and neurotransmitter levels (GABA⁺, glutamate+glutamine) in 2 key SN nodes, anterior insular (aIns_R) and anterior mid-cingulate cortices. In addition, examinations were repeated in chronic back pain patients after a 4-week interdisciplinary multimodal pain treatment and in healthy subjects after 4 weeks to explore longitudinal, treatment-mediated changes in target variables. The aIns_R and, to a lesser extent, the anterior mid-cingulate of patients exhibited significantly reduced wCC accompanied by a spectral power shift from a lower to a higher frequency band, indicating a desynchronization of their neuronal activity within the SN, possibly because of increased spontaneous activations. Without revealing neurotransmitter differences, patients alone showed significant positive associations between local GABA⁺ levels and wCC in aIns_R, suggesting a stronger dependence of node synchronization on the inhibitory tone in the chronic pain state. However, this needs to be explored in the future using magnetic resonance spectroscopy techniques that are more sensitive to detecting subtle neurotransmitter changes and also allow multifocal characterization of neurotransmitter tone.

Abnormal emotional reactions of the brain in patients with facial nerve paralysis have not yet been reported. This study aims to investigate this issue by applying a machine-learning algorithm that discriminates brain emotional activities that belong either to patients with facial nerve paralysis or to healthy controls. Beyond this, we assess an emotion rating task to determine whether there are differences in their experience of emotions. MEG signals of 17 healthy controls and 16 patients with facial nerve paralysis were recorded in response to picture stimuli in three different emotional categories (pleasant, unpleasant, and neutral). The selected machine learning technique in this study was the logistic regression with LASSO regularization. We demonstrated significant classification performances in all three emotional categories. The best classification performance was achieved considering features based on event-related fields in response to the pleasant category, with an accuracy of 0.79 (95% CI (0.70, 0.82)). We also found that patients with facial nerve paralysis rated pleasant stimuli significantly more positively than healthy controls. Our results indicate that the inability to express facial expressions due to peripheral motor paralysis of the face might cause abnormal brain emotional processing and experience of particular emotions.