Locus coeruleus (LC) sends widespread outputs to many brain regions to modulate diverse functions, including sleep/wake states, attention, and the general anesthetic state. The paraventricular thalamus (PVT) is a critical thalamic area for arousal and receives dense tyrosine-hydroxylase (TH) inputs from the LC. Although anesthesia and sleep may share a common pathway, it is important to understand the processes underlying emergence from anesthesia. In this study, we hypothesize that LC TH neurons and the TH:LC-PVT circuit may be involved in regulating emergence from anesthesia. Only male mice are used in this study. Here, using c-Fos as a marker of neural activity, we identify LC TH expressing neurons are active during anesthesia emergence. Remarkably, chemogenetic activation of LC TH neurons shortens emergence time from anesthesia and promotes cortical arousal. Moreover, enhanced c-Fos expression is observed in the PVT after LC TH neurons activation. Optogenetic activation of the TH:LC-PVT projections accelerates emergence from anesthesia, whereas, chemogenetic inhibition of the TH:LC-PVT circuit prolongs time to wakefulness. Furthermore, optogenetic activation of the TH:LC-PVT projections produces electrophysiological evidence of arousal. Together, these results demonstrate that activation of the TH:LC-PVT projections is helpful in facilitating the transition from isoflurane anesthesia to an arousal state, which may provide a new strategy in shortening the emergence time after general anesthesia.
Background Sarcopenia has been confirmed as a poor prognostic indicator of lung cancer. However, the lack of abdominal computed tomography (CT) hindered the application to assess the status of sarcopenia. The purpose of this study was to assess the ability of chest CT radiomics combined with machine learning classifiers to identify sarcopenia in advanced non‐small cell lung cancer (NSCLC) patients. Methods This study retrospectively analyzed CT images of 99 patients with NSCLC. Skeletal muscle radiomics were extracted from a single axial slice of the chest CT scan at the 12th thoracic vertebrae level. In total, 854 radiomic and clinical features were obtained from each patient. Feature selection was conducted with FeatureSelector module, optimal key features were fed into the lightGBM classifier for model construction, and Bayesian optimization was adopted to tune hyperparameters. The model's performance was evaluated by specificity, sensitivity, accuracy, precision, F1‐score, Matthew's correlation coefficient (MCC), Cohen's kappa coefficient (Kappa), and AUC. Results A total of 40 patients were found to have sarcopenia. Five optimal features were selected. In the base lightGBM model, the specificity, sensitivity, accuracy, precision, F1‐score, AUC, MCC, Kappa of validation set were 0.889, 0.750, 0.833, 0.818, 0.783, 0.819, 0.649, 0.648, respectively. After Bayesian hyperparameter tuning, the optimized lightGBM model achieved better prediction performance, and the corresponding values were 0.944, 0.833, 0.900, 0.909, 0.870, 0.889, 0.791, 0.789, respectively. Conclusions Chest CT‐based radiomics has the potential to identify sarcopenia in NSCLC patients with the lightGBM classifier, and the optimal lightGBM model via Bayesian hyperparameter tuning demonstrated better performance. Key points Significant findings of the study Our study demonstrates that chest CT‐based radiomics combined with lightGBM classifier has the ability to identify sarcopenia in NSCLC patients. What this study adds Skeletal muscle radiomics would be a potential biomarker for sarcopenia identity in NSCLC patients.
Background and Purpose Dopamine is well‐known to contribute to emergence from anesthesia. Previous studies have demonstrated that the paraventricular thalamus (PVT) in the midline nuclei is crucial for wakefulness. Moreover, the PVT receives dopaminergic projections from the brainstem. Therefore, we hypothesize that the dopaminergic signaling in the PVT plays a role in emergence from isoflurane anesthesia. Methods We used c‐Fos immunohistochemistry to reveal the activity of PVT neurons in three groups: The first group (iso + EM ‐ ) underwent the anesthesia protocol and was sacrificed before emergence. The second group (iso + EM + ) underwent passive emergence from the same anesthesia protocol. The last group (oxy + ) received oxygen. D2‐like agonist quinpirole (2 or 4 mM) or D2‐like antagonist raclopride (2 or 5 mM) was microinjected into the PVT, and their effects on emergence and induction time were analyzed. Surface cortical electroencephalogram (EEG) recordings were used to explore the effects of quinpirole injection into the PVT on cortical excitability during isoflurane anesthesia. The activity of PVT neurons after quinpirole injection was assessed by c‐Fos immunohistochemistry. Results The number of c‐Fos‐positive nuclei for the iso + EM + group was significantly higher than the oxy + and iso + EM ‐ groups. Application of quinpirole (4 mM) into the PVT shortened emergence time compared with the saline group ( p < .01). In contrast, administration of raclopride (2 mM) delayed emergence time ( p < .05). Neither quinpirole nor raclopride exerted an effect on induction time. EEG analyses showed that quinpirole (4 mM) decreased the burst suppression ratio during isoflurane anesthesia ( p < .01). The number of c‐Fos‐positive nuclei for the quinpirole (4 mM) group was significantly higher than saline group ( p < .01). Conclusions Our findings suggest that the activity of PVT neurons is enhanced after emergence from anesthesia, and the dopaminergic signaling in the PVT may facilitate emergence from isoflurane anesthesia.
Background The thalamus is an important deep brain structure for the synchronization of brain rhythm and the integration of cortical activity. Human brain imaging and computational modeling have non-invasively revealed its role in maintaining the cortical network architecture and functional hierarchy. Purpose The objective of this study was to identify the effect of unilateral thalamic damage on the human brain intrinsic functional architecture. Patients and methods We collected an 8-minute resting-state functional magnetic resonance imaging (R-fMRI) data on a 3.0 T magnetic resonance scanner for all the participants: a preoperative patient with left thalamus destroyed by anaplastic astrocytoma (WHO grade III type of astrocytoma) and 20 matched healthy controls. The R-fMRI data was analyzed for functional connectivity and amplitude of spontaneous fluctuations. Results The patient showed prominent decrease in functional connectivity within primary sensory networks and advanced cognitive networks, and extensive alterations in between-network coupling. Further analysis of the amplitude of spontaneous activity suggested significant decrease especially in the topographies of default mode network and the Papez circuit. Conclusion This result provided evidence about the consequences of thalamic destruction on the correlation and landscape of spontaneous brain activity, promoting our understanding of the effects of thalamic damage on large-scale brain networks.
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