Accepted

Chronic pain remains an intractable condition in millions of patients worldwide. Spontaneous ongoing pain is a major clinical problem of chronic pain and is extremely challenging to diagnose and treat compared to stimulus-evoked pain. Although extensive efforts have been made in preclinical studies, there still exists a mismatch in pain type between the animal model and humans (i.e., evoked vs. spontaneous), which obstructs the translation of knowledge from preclinical animal models into objective diagnosis and effective new treatments. Here, we developed a deep learning algorithm, designated AI-bRNN (Average training, Individual test-bidirectional Recurrent Neural Network), to detect spontaneous pain information from brain cellular Ca activity recorded by two-photon microscopy imaging in awake, head-fixed mice. AI-bRNN robustly determines the intensity and time points of spontaneous pain even in chronic pain models and evaluates the efficacy of analgesics in real time. Furthermore, AI-bRNN can be applied to various cell types (neurons and glia), brain areas (cerebral cortex and cerebellum) and forms of somatosensory input (itch and pain), proving its versatile performance. These results suggest that our approach offers a clinically relevant, quantitative, real-time preclinical evaluation platform for pain medicine, thereby accelerating the development of new methods for diagnosing and treating human patients with chronic pain.

We investigated the neural correlates for chronic cancer pain conditions by retrospectively analyzing whole brain regions on 18F-fluoro-2-deoxyglucose-positron emission tomography images acquired from 80 patients with head and neck squamous cell carcinoma and esophageal cancer. The patients were divided into three groups according to perceived pain severity and type of analgesic treatment, namely patients not under analgesic treatment because of no or minor pain, patients with good pain control under analgesic treatment, and patients with poor pain control despite analgesic treatment. Uncontrollable cancer pain enhanced the activity of the hippocampus, amygdala, inferior temporal gyrus, and temporal pole. Metabolic connectivity analysis further showed that amygdala co-activation with the hippocampus was reduced in the group with poor pain control and preserved in the groups with no or minor pain and good pain control. The increased although imbalanced activity of the medial temporal regions may represent poor pain control in patients with cancer. The number of patients who used anxiolytics was higher in the group with poor pain control, whereas the usage rates were comparable between the other two groups. Therefore, further studies should investigate the relationship between psychological conditions and pain in patients with cancer and analyze the resultant brain activity.Trial registration: This study was registered at clinicaltrials.gov on 9/3/20 (NCT04537845).

Laser-assisted drug delivery (LADD) is used for various medical and cosmetic applications. However, there is insufficient evidence-based guidance to assist clinicians performing LADD.

The Nociception Level index (NOL™) is a multiparameter index, based on artificial intelligence for the monitoring of nociception during anesthesia. We studied the influence of NOL-guided analgesia on postoperative pain scores in patients undergoing major abdominal surgery during sevoflurane/fentanyl anesthesia. This study was designed as a single-center, prospective randomized, controlled study. After Institutional Review Board approval and written informed consent, 75 ASA 1-3 adult patients undergoing major abdominal surgery, were randomized to NOL-guided fentanyl dosing (NOL) or standard care (SOC) and completed the study. The sevoflurane target MAC range was 0.8-1.2. In the NOL-guided group (N = 36), when NOL values were > 25 for at least 1 min, a weight adjusted fentanyl bolus was administered. In the control group (N = 39) fentanyl administration was based on hemodynamic indices and clinician judgement. After surgery, pain, was evaluated using the Numerical Rating Scale (NRS) pain scale, ranging from 0 to 10, at 15 min intervals for 180 min or until patient discharge from the PACU. Median postoperative pain scores reported were 3.0 [interquartile range 0.0-5.0] and 5.0 [3.0-6.0] at 90 min in NOL-guided and control groups respectively (Bootstrap corrected actual difference 1.5, 95% confidence interval 0.4-2.6). There was no difference in postoperative morphine consumption or intraoperative fentanyl consumption. Postoperative pain scores were significantly improved in nociception level index-guided patients. We attribute this to more objective fentanyl dosing when timed to actual nociceptive stimuli during anesthesia, contributing to lower levels of sympathetic activation and surgical stress. Clinicaltrials.gov identifier: NCT03970291 date of registration May 31, 2019.

Chronic pain relief remains an unmet medical need. Current research points to a substantial contribution of glia-neuron interaction in its pathogenesis. Particularly, microglia play a crucial role in the development of chronic pain. To better understand the microglial contribution to chronic pain, specific regional and temporal manipulations of microglia are necessary. Recently, two new approaches have emerged that meet these demands. Chemogenetic tools allow the expression of designer receptors exclusively activated by designer drugs (DREADDs) specifically in microglia. Similarly, optogenetic tools allow for microglial manipulation via the activation of artificially expressed, light-sensitive proteins. Chemo- and optogenetic manipulations of microglia in vivo are powerful in interrogating microglial function in chronic pain. This review summarizes these emerging tools in studying the role of microglia in chronic pain and highlights their potential applications in microglia-related neurological disorders.