K-ras –mutant lung adenocarcinoma (KM-LUAD) is associated with abysmal prognosis and is tightly linked to tumor-promoting inflammation. A human mAb, canakinumab, targeting the proinflammatory cytokine IL-1β, significantly decreased the risk of lung cancer in the Canakinumab Anti-inflammatory Thrombosis Outcomes Study. Interestingly, we found high levels of IL-1β in the lungs of mice with K-ras ^G12D –mutant tumors (CC-LR mice). Here, we blocked IL-1β using an anti–IL-1β mAb in cohorts of 6- or 14-week-old CC-LR mice to explore its preventive and therapeutic effect, respectively. IL-1β blockade significantly reduced lung tumor burden, which was associated with reprogramming of the lung microenvironment toward an antitumor phenotype characterized by increased infiltration of cytotoxic CD8 ⁺ T cells (with high IFN-γ and granzyme B expression but low programmed cell death 1 [PD-1] expression) while suppressing neutrophils and polymorphonuclear (PMN) myeloid-derived suppressor cells. When querying the Cancer Genome Atlas data set, we found positive correlations between IL1B expression and infiltration of immunosuppressive PMNs and expression of their chemoattractant, CXCL1 , and PDCD1 expressions in patients with KM-LUAD. Our data provide evidence that IL-1β blockade may be a preventive strategy for high-risk individuals and an alternative therapeutic approach in combination with currently available treatments for KM-LUAD.

Purpose: To develop a deep learning (DL) model for obstructive sleep apnea (OSA) detection and severity assessment and provide a new approach for convenient, economical, and accurate disease detection. Methods: Considering medical reliability and acquisition simplicity, we used electrocardiogram (ECG) and oxygen saturation (SpO₂) signals to develop a multimodal signal fusion multiscale Transformer model for OSA detection and severity assessment. The proposed model comprises signal preprocessing, feature extraction, cross-modal interaction, and classification modules. A total of 510 patients who underwent polysomnography were included in the hospital dataset. The model was tested on hospital and public datasets. The hospital dataset was utilized to demonstrate the applicability and generalizability of the model. Two public datasets, Apnea-ECG dataset (consisting of 8 recordings) and UCD dataset (consisting of 21 recordings), were used to compare the results with those of previous studies. Results: In the hospital dataset, the accuracy (Acc) values of per-segment and per-recording detection were 91.38 and 96.08%, respectively. The Acc values for mild, moderate, and severe OSA were 90.20, 88.24, and 92.16%, respectively. The Bland‒Altman plots revealed the consistency of the true apnea–hypopnea index (AHI) and the predicted AHI. In the public datasets, the per-segment detection Acc values of the Apnea-ECG and UCD datasets were 95.04 and 90.56%, respectively. Conclusion: The experiments on hospital and public datasets have demonstrated that the proposed model is more advanced, accurate, and applicable in OSA detection and severity assessment than previous models.

Purpose: Aimed to analyze the developmental characteristics of craniofacial structures and soft tissues in children with obstructive sleep apnea (OSA) and to establish and evaluate prediction model. Methods: It's a retrospective study comprising 747 children aged 2-12 years (337 patients and 410 controls) visited the Department of Otolaryngology-Head and Neck Surgery, the Second Affiliated Hospital of Xi'an Jiaotong University (July 2017 to March 2024). Lateral head radiographs were obtained to compare the cephalometric measurements. The clinical prediction model was constructed using LASSO regression analysis. We analyzed 300 children from the Xi'an Children's Hospital for external validation. Results: Children with OSA had a higher body mass, a higher tonsil grade, larger AN ratio (ratio of the adenoids to the skeletal upper airway width), larger radius of the tonsils, a smaller angle between the skull base and maxilla (SNA) and smaller angle between the skull base and mandible (SNB), a larger distance from the hyoid to the mandibular plane (H-MP) and smaller distance between the third cervical vertebra and hyoid (H-C), a larger thickness of the soft palate (SPT) and smaller inclination angle of the soft palate than those of the controls (all p < 0.05). A prediction model was constructed for 2-12 years group (AUC of 0.812 [95% CI: 0.781-0.842]). Age-specific prediction models were developed for preschool children (AUC of 0.769 [95% CI: 0.725-0.814]), for school-aged children (AUC of 0.854 [95% CI: 0.812-0.895]). Conclusion: Our study findings support the important role of craniofacial structures such as the hyoid, maxilla, mandible, and soft palate in pediatric OSA. Age-stratified predictive models for pediatric OSA indicated varying parameters across different age groups which underscore the necessity for stratifying by age in future research. The prediction model designed will greatly assist health care practitioners with rapidly identifying.

Background: As an important neuroprotective factor, the brain-derived neurotrophic factor (BDNF) may have a key role in cognitive impairment in children with sleep-disordered breathing (SDB). The main aim of this study was to compare the levels of BDNF and tyrosine kinase receptor B (TrkB) in normal children and those with obstructive sleep apnea (OSA) and primary snoring (PS) and to explore a possible link between BDNF/TrkB, inflammation, and SDB with cognitive impairment in children.Methods: A total of 44 OSA children and 35 PS children who completed polysomnography between October 2017 and October 2019 were enrolled. At the same time, 40 healthy children during the same period were included as a control. Enzyme-linked immunosorbent assay was used to measure serum indices of BDNF, TrkB, interleukin-1beta (IL-1β), and tumor necrosis factor-alpha (TNF-α). Correlation and pooled analyses were performed between the cognitive scores and four serological indicators. Logistic regression was used to analyze the risk factors for cognitive impairment.Results: Significant differences were found in serum BDNF, TrkB, IL-1β, and TNF-α between the three groups (all P < 0.01). The serum BDNF and TrkB in the OSA and PS groups were lower than those in the control group, whereas the serum IL-1β and TNF-α were higher than those in the control group (all P < 0.05). Moreover, among these four indices, the strongest correlation was found between BDNF and the Chinese Wechsler Intelligence Scale (all P < 0.05). Logistic regression analysis revealed a correlation between OSA status, TrkB, and course of mouth breathing and cognitive status.Conclusion: The levels of serum BDNF and TrkB were related to cognitive impairment in children with SDB. Also, BDNF and TrkB could be used as noninvasive and objective candidate markers and predictive indices of cognitive impairment in children with SDB.

Purpose: This study unveils the complex interplay among obstructive sleep apnea (OSA), thyroid function, and morphological changes. Methods: Data from 1,102 patients were collected retrospectively from the Department of Otorhinolaryngology—Head and Neck Surgery of the Second Affiliated Hospital of Xi’an Jiaotong University from 2012 to 2023. The patients were divided into severe and non-severe OSA groups according to their polysomnography results. The data were analyzed by sex and age stratification. Results: Serum free triiodothyronine (FT3), total triiodothyronine (TT3), and reverse triiodothyronine (RT3) were higher in severe OSA group in the total population (p < 0.05). Similar trends were observed in male but not in female. FT3 and TT3 are higher in the severe group in the nonelderly population (age < 60) (p < 0.05), and RT3 is higher in the severe group in the elderly population (age ≥ 60) (p < 0.05). In addition, we first reveal that RT3 is associated with the diameter of the left inferior thyroid artery (L-ITA) (r=0.394, p < 0.05) and lowest transcutaneous oxygen saturation at night (lowest SpO₂) (r=− 0.269, p < 0.05). The severe OSA group showed larger thyroid volume and isthmus length, as well as the thicker ITA diameter and lower left thyroid lobe resistance index (RI) (all p < 0.05). Conclusion: Our study demonstrates a significant association between thyroid function/morphology and OSA, with distinct sex- and age-related differences. Reduced RI in severe OSA suggests its clinical utility in assessing vascular health. Increased thyroid volume and isthmus length in severe OSA may reflect ITA-related changes. These findings support our prior observations of rising thyroid hormone levels with OSA progression and highlight the need for sex- and age-stratified analyses. Integrated evaluation of thyroid function and morphology is essential for understanding OSA-thyroid pathophysiology.

Purpose: This study investigated cognitive impairment in children with obstructive sleep apnea (OSA) by evaluating the utility of sleep apnea-specific hypoxic burden (SASHB) and sleep breathing impairment index (SBII) compared to the obstructive apnea-hypopnea index (OAHI).Methods: A retrospective analysis included 141 children with suspected OSA from Xi'an Jiaotong University Second Affiliated Hospital (October 2021–October 2024), categorized into OSA (n = 104) and non-OSA (n = 37) groups based on OAHI. Demographic, polysomnography (PSG), and event-related potential (ERP) data were collected. Cognitive function (full, verbal, and performance IQ: FIQ, VIQ, PIQ) was assessed using the China-Wechsler Intelligence Scale (C-WISC). Correlations between cognitive scores, ERP parameters, OAHI, SASHB, and SBII were analyzed.Results: OSA children exhibited higher rates of snoring/sleep suffocation, prolonged apnea/hypoventilation durations, reduced mean/minimum SaO2, lower REM sleep, and elevated N3 sleep. OAHI and SASHB were higher in the OSA group, but SBII showed no group difference. OSA children had prolonged P300/N100 latencies and lower FIQ, VIQ, and PIQ scores. FIQ inversely correlated with OAHI, SASHB, and SBII; after adjusting for age, sex, and BMI, FIQ remained negatively associated with SBII. SASHB correlated with FIQ only in children <6 years, while OAHI showed no significant correlation. VIQ in younger children negatively correlated with SASHB/SBII, but only with OAHI in older children. PIQ in younger children correlated with OAHI, while no correlations existed in older children. P300 latency positively correlated with OAHI; other ERP parameters showed no associations.Conclusion: OSA children demonstrate significant cognitive decline and ERP abnormalities. SASHB and SBII exhibit stronger correlations with cognitive impairment than OAHI, particularly in younger children, highlighting their potential as precise metrics for evaluating cognitive deficits in pediatric OSA.