Background: The primary goal of this study was to investigating the symptoms, in addition to the reflux-related laryngopharynx inflammation performance of asymptomatic, volunteers, and verified the ‘normal point’. Methods: A total of 91 asymptomatic subjects were recruited for this cross-sectional study between March 2016 and September 2016. Participants completed the reflux symptom index (RSI) assessment and underwent laryngostroboscopic examination using a rigid endoscope. Their RFS were graded according to the laryngeal findings. The distribution and the relationship of the RSI and the RFS were analyzed. Results: The mean RSI of individuals was 2.24 ± 2.34 [95% confidence interval (CI) = 1.75, 2.72], and the mean RFS of individuals was 5.78 ± 1.74 (95% CI = 5.42, 6.15). The Pearson product–moment correlation coefficient of the RSI and RFS scores was –0.084 (n = 91, p = .428). Conclusions: Asymptomatic people could present relatively high RFS scores, and no linear relationship existed between RSI and RFS.

Objective: Using rabbit models, this study simulated the laryngopharynx’s response to the synergistic effects of various acidic reflux environments and pepsin to investigate the response mechanism underlying weak acid reflux and pepsin in the mucosal barrier injury of laryngopharyngeal reflux. Methods: The rabbits were divided into six groups, and the original larynx was recorded for each group. During the study period, rabbits were sprayed with different doses of acid and pepsin solutions and monitored for hypopharyngeal mucosal transient impedance before and after modeling. After the experiment, laryngeal mucosal tissues were collected, observed using hematoxylin and eosin staining, and assessed for E-cadherin expression. The width of the intercellular space and lanthanum staining penetrating the intercellular space were also observed using electron microscopy. Results: Eight weeks post-modeling, evidence of laryngopharyngeal mucosa inflammatory responses was observed in each group. Downregulation of E-cadherin expression significantly positively correlated with acid strength (p < 0.05). The pepsin and acid intervention groups showed a significantly widened space between mucosal epithelial cells in the posterior ring area (p < 0.05). Meanwhile, in the experimental group, a large amount of stained lanthanum penetrated the intercellular spaces; however, no significant difference was observed in the mucosal impedance (MI). Conclusion: This study demonstrated that acid, weak acid, and pepsin could damage the laryngeal mucosal barrier; pepsin was an independent factor associated with tissue damage; the downregulation of hypopharyngeal cadherin was associated with acid-intensity exposure. Transient LP-MI cannot be applied directly.

Background: Cervical lymph node metastasis (LNM) is a significant factor that leads to a poor prognosis in laryngeal cancer. Early-stage supraglottic laryngeal cancer (SGLC) is prone to LNM. However, research on risk factors for predicting cervical LNM in early-stage SGLC is limited. This study seeks to create and validate a predictive model through the application of machine learning (ML) algorithms.Methods: The training set and internal validation set data were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. Data from 78 early-stage SGLC patients were collected from Fujian Provincial Hospital for independent external validation. We identified four variables associated with cervical LNM and developed six ML models based on these variables to predict LNM in early-stage SGLC patients.Results: In the two cohorts, 167 (47.44%) and 26 (33.33%) patients experienced LNM, respectively. Age, T stage, grade, and tumor size were identified as independent predictors of LNM. All six ML models performed well, and in both internal and independent external validations, the eXtreme Gradient Boosting (XGB) model outperformed the other models, with AUC values of 0.87 and 0.80, respectively. The decision curve analysis demonstrated that the ML models have excellent clinical applicability.Conclusions: Our study indicates that combining ML algorithms with clinical data can effectively predict LNM in patients diagnosed with early-stage SGLC. This is the first study to apply ML models in predicting LNM in early-stage SGLC patients.

Pepsin serves as a potential biomarker for laryngopharyngeal reflux disease (LPRD). The reported methods for detecting pepsin still have limitations, such as long reaction times and low sensitivity. Therefore, it is crucial to develop a rapid, simple and sensitive detection method. In this study, a fluorescence immunochromatographic test strip was designed for point-of-care diagnostics of LPRD. To obtain optimal fluorescence immunochromatographic conditions, key experimental factors, including microsphere particle size, binding pH, and resuspension dilution ratio, were systematically evaluated. The optimal fluorescent microsphere size was determined to be 300 nm, the most suitable reaction pH was 8.0, and the ideal resuspension solution to storage solution ratio was 1 : 4. Under these optimal conditions, the sensor had a linear range of 2.5–100.0 ng mL⁻¹ and a detection limit of 1.9 ng mL⁻¹. The relative standard deviation was below 15% for both intra- and inter-batch reproducibility. Under accelerated damage conditions at 37 °C, the test value of the test strip could be kept basically unchanged for 14 days. There was no cross-reactivity of the test strip with pepsinogen I, pepsinogen II and other interferents. In the actual sample detection, the recovery rate was between 85% and 115%. Furthermore, the proposed method was demonstrated to be green and to exhibit strong applicability based on the evaluation using the AGREEprep and the BAGI. In addition, the method has the advantages of high sensitivity, accuracy, greenness and applicability, which can meet the needs of rapid quantitative on-site detection.