Yongzheng Han

Painful diabetic neuropathy (PDN) is characterized by hyperalgesia and neuronal hyperexcitability. Although gut microbiota dysbiosis has been found in PDN, the mechanisms by which the microbiota influence PDN remain largely unknown. Gut microbiota and its metabolites impacted PDN were investigated with multi-omics analyses in a rat model of high-fat diet/low-dose streptozotocin-induced type 2 diabetes. A significant decrease in the gut microbiota, including Clostridium, Lactobacillus, and Bifidobacterium, as well asin serum level of hyodeoxycholic acid (HDCA), was found in the PDN rats. Transplantation of fecal microbiota from the PDN to normal rats recapitulated the PDN phenotype, and HDCA treatment was able to alleviate the hyperalgesia of PDN. RNA sequencing and molecular assays showed that HDCA suppressed neuroinflammation by inhibiting the TLR4/MyD88/NF-κB pathway and reducing proinflammatory cytokine production in the DRG. These findings identify HDCA as a microbiota-derived metabolite that ameliorates PDN via neuroinflammation inhibition and highlight its therapeutic potential.

Objectives: To identify prefrailty and mild cognitive impairment (MCI) in patients undergoing total hip/knee replacement using preoperative ultrasound measurements of muscle dimensions and stiffness. Methods: This pilot study was conducted at a large tertiary public hospital in Beijing, China, and included 121 consecutive patients with hip or knee osteoarthritis scheduled for total hip or knee replacement [median age 71 years, interquartile range (IQR) 5 years; 94 women, 77.7%]. Preoperative assessments included measurements of the dimensions and stiffness of the biceps brachii (BB) using grey scale ultrasound (US) and shear wave elastography (SWE). Patients were preoperatively assessed for prefrailty and mild cognitive impairment (MCI) based on FRAIL scale and Montreal Cognitive Assessment (MoCA) combined with the Clinical Dementia Rating Scale (CDR). Prospective subgroup analyses stratified by gender were performed to identify parameters with statistically significant differences between the non-prefrail and prefrail groups, as well as between the non-MCI and MCI groups. Results: Subgroup analysis by gender showed that thickness of BB on both dominant and non-dominant side in prefrail group from male patients were significantly lower than that in non-frail group. The thickness of the BB on the non-dominant side in predicting prefrailty among male patients had the highest AUC (0.824, 95% CI: 0.627–1.000), with an optimal cut-off value of 1.85 cm, achieving sensitivity of 77.8%, specificity of 66.7%. However, this finding is exploratory given the small male prefrail subgroup ( n = 9) and requires validation in adequately powered cohorts. In female participants, no parameters showed a significant difference between the non-prefrail and prefrail groups. Additionally, no significant differences were observed in ultrasound measurements between MCI and non-MCI groups. Conclusion: In this pilot study, preoperative US measurements of BB thickness demonstrated preliminary promise for predicting prefrailty among male patients undergoing total hip/knee replacement. These findings are hypothesis-generating and require confirmation in larger, independent cohorts. However, this approach showed limited utility in female participants and was not effective in predicting MCI. Clinical Trial Registration : https:// www.chictr.org.cn/showproj.aspx?proj=177048 , identifier ChiCTR2200062483.

Continuous monitoring of core temperature and blood perfusion is essential during general anesthesia, yet current workflows leave a critical gap during induction, before invasive probes can be placed. We present a compact, skin-interfaced thermal sensing platform for non-invasive monitoring throughout the anesthetic process. The device combines thermal-guiding materials with real-time heat-transfer modeling and inversion algorithms to estimate tissue thermal conductivity, blood perfusion, core temperature, and surface heat flux. Phantom and human-subject experiments showed measurement errors within ±10% or ±0.1 °C. During laparoscopic surgery, the estimated core temperature agreed well with invasive esophageal measurements. Long-term monitoring across sleep, exercise, and rest also demonstrated robust performance compared with a conventional dual-heat-flux sensor (r > 0.85). This multimodal platform may provide a reliable alternative for perioperative thermal monitoring and support broader applications in personalized thermal health management.

Background: This study aimed to explore the efficacy and safety of remimazolam vs. propofol for sedation during video laryngoscopy in cervical spondylosis patients with suspected difficult laryngoscopy. Methods: In this single-center, prospective, randomized controlled study, 85 patients with Modified Mallampati class III or IV and limited cervical spine mobility were recruited and randomly assigned (1:1 ratio) to receive either remimazolam or propofol sedation. The primary outcome was the incidence of hypoxemia (SpO₂< 90% for >10 s). Secondary outcomes included sedation efficacy and side effects. Results: The incidence of hypoxemia was significantly lower in the remimazolam group (13.6%) than in the propofol group (39.0%; P = 0.008), with an absolute risk difference of 25.4% (95% confidence interval 0.073–0.434). The propofol group required more additional airway interventions ( P = 0.007). After adjusting for age, gender, and body mass index, propofol was associated with higher odds of hypoxemia (adjusted odds ratio = 4.602; 95% confidence interval 1.330–15.922; P = 0.016) and more advanced airway interventions (adjusted odds ratio = 4.598; 95% confidence interval 1.395–15.152; P = 0.012). Injection pain occurred in 31.7% of propofol patients but was absent in the remimazolam group ( P < 0.001). Conclusions: Remimazolam provides effective and safe sedation for video laryngoscopy in cervical spondylosis patients with suspected difficult laryngoscopy, significantly reducing the incidence of hypoxemia and the need for airway interventions compared to propofol. Trial registration: This protocol was approved by Peking University Third Hospital Medical Science Research Ethics Committee (IRB00006761–M2024420, June 2024) and was prospectively registered with the Chinese Clinical Trial Registry (ChiCTR2400086137, June 2024).

Background: The identification of difficult laryngoscopy is a critical skill for anesthesiologists, particularly in high-risk procedures such as cervical spine surgery, which demands heightened accuracy in preoperative airway assessment. This study developed a deep learning algorithm, the double-pose feature clustering network (DPFCNet), designed to improve the identification of patients with difficult laryngoscopy through comprehensive analysis of neutral and extended cervical spine x-ray images. Methods: In this prospective cohort study, 14,407 patients who underwent elective cervical spine surgery under general anesthesia (July 2016 to July 2023) were initially enrolled. Following rigorous screening, 1,568 participants were eligible and included in the analysis, comprising 319 difficult laryngoscopy cases and 1,249 easy laryngoscopy cases. The study evaluated the effectiveness of a deep learning model for identifying difficult laryngoscopy that was developed using a ResNet-based feature extraction module with dual-position image fusion technology and systematically compared it against conventional bedside assessments using area under the receiver operating characteristic curve (AUC) analysis. Results: Conventional clinical indicators showed poor predictive capacity for difficult laryngoscopy: thyromental distance (AUC = 0.594), neck circumference (AUC = 0.662), inter-incisor gap (AUC = 0.607), and modified Mallampati test (AUC = 0.624). Their combination achieved AUC = 0.743. In contrast, DPFCNet considerably outperformed conventional methods with AUC = 0.866, demonstrating superior discriminative power. Conclusion: This study employed a deep learning model for the comprehensive analysis of both neutral and extended cervical spine x-ray images, considerably improving the prediction accuracy of difficult laryngoscopy. DPFCNet provides an effective decision-support tool for preoperative risk stratification in cervical spondylosis patients.

Minimally invasive coronary artery bypass grafting (MIDCAB) requires effective left lung isolation, yet evidence comparing video-imaging single-lumen trach

Background: Preoperative insomnia is prevalent among elderly arthroplasty patients, yet its impact on postoperative sleep disturbance (PSD) remains underexplored. This study investigated whether preexisting insomnia exacerbates postoperative sleep fragmentation in total hip/knee arthroplasty (THA/TKA) patients under spinal anesthesia. Methods: In this prospective cohort study 121 patients aged ≥65 undergoing THA/TKA were stratified by preoperative insomnia. Sleep was assessed via subjective metrics including Pittsburgh Sleep Quality Index (PSQI), Athens Insomnia Scale (AIS) and Insomnia Severity Index (ISI). Meanwhile, the EEG-based monitor and actigraphy were used to assess the objective sleep quality and conduct sleep staging. Results: Pre-existing insomnia exacerbates postoperative sleep fragmentation, manifested by persistently elevated microarousals (operative night to postoperation day2, POD2) and prolonged sleep latency. Selective REM suppression occurs in insomnia patients during the acute postoperative phase (operative night and POD1), independent of NREM duration alterations. Subjective sleep quality assessments revealed that the insomnia group demonstrated significantly higher AIS and ISI scores compared to the non-insomnia group. Conclusion: Preoperative insomnia independently exacerbates postoperative sleep fragmentation in elderly arthroplasty patients. The study was registered with the Chinese Clinical Trial Registry (Registration No. ChiCTR2400085184) on June 8, 2024.