The prevalence of common allergic diseases, including allergic rhinitis, asthma, atopic dermatitis, and food allergy, has increased dramatically with rising industri-alization in China, leading to a significant socio-economic burden. These allergic diseases are complex disorders influenced by both environmental and genetic factors. Epidemiological evidence indicates a parallel increase in the prevalence of other systemic diseases during the same period as the allergic disease epidemic, suggesting that these conditions may share common genetic mechanisms and potentially have a causal relationship. This review summarizes recent epidemio-logical studies on common allergic diseases in China, highlighting interrelated changes in demography, allergen spectrum, and the environmental and genetic implications. It aims to enhance our understanding of these conditions, contributing to the development of a robust public health monitoring network and the exploration of strategies for the prevention, control, and treatment of common allergic diseases in the Chinese population.

Objective: This review evaluates the worldwide use of artificial intelligence (AI) for the diagnosis and treatment of voice disorders.

Methods: An electronic search was completed in Embase, Pubmed, Ovid MEDLINE, Scopus, Google Scholar, and Web of Science. Studies in English from 2019 to 2024 evaluating the use of AI in detection and management of voice disorders were included. Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines were followed.

Results Eighty-one studies were recognized. Thirty-three studies were chosen and screened for quality assessment. Of these, 16 studies used AI to determine normal versus pathological voice. The convolutional neural network (CNN) was the most employed algorithm among all machine learning algorithms.

Conclusion This review revealed significant interest worldwide in utilizing AI in detection of voice disorders. Gaps included the use of limited, inconsistent data sets, lack of validation, and emphasis on detection rather than treatment of the voice disorder. These are areas of opportunity for AI techniques to improved diagnostic accuracy.

Objective: To evaluate the 1-year efficacy of subcutaneous immunotherapy (SCIT) in treating dust mite-induced allergic rhinitis (AR) and establish objective biomarkers for efficacy monitoring.

Methods: Fifty-nine AR patients underwent 1-year SCIT. Subjective symptoms were assessed via total nasal symptom score (TNSS), combined symptom/medication score (CSMS), and mini rhinoconjunctivitis quality of life questionnaire (MiniRQLQ). Serum total immunoglobulin E (tIgE), Dermatophagoides species-specific IgE (Der p-sIgE), and component-specific IgE (Der p1/2/10/23) were measured. IgE-facilitated allergen binding (IgE-FAB) assay evaluated blocking antibody activity.

Results The mean TNSS, CSMS, and MiniRQLQ scores were significantly reduced by 28.60% (p < 0.001), 28.60% (p = 0.006), and 24.30% (p < 0.001) respectively after 1 year of SCIT treatment. SCIT treatment significantly elevated serum tIgE and Der p sIgE levels (p < 0.001), with a pronounced increase in component-specific IgE positivity for Der p1 and Der p23 (p < 0.001). The IgE-FAB assay demonstrated that the average suppression of IgE-allergen binding in serum by 1-year SCIT was 4.48% (p < 0.001).

Conclusion SCIT markedly reduces subjective symptoms in patients with dust mite AR over a 1-year treatment period. Component-sIgE levels and IgE-FAB inhibition could function as objective biomarkers for assessing immunotherapy efficacy, thus facilitating tailored clinical interventions.

Due to the limited regenerative capacity in adult mammals, the loss of vestibular hair cells (HCs) leads to balance disorders. In this study, we chronologically reprogrammed adult vestibular supporting cells (SCs) via bimodal regulation of Notch signaling, mimicking dynamic changes in Notch signaling during inner ear development. We found that activating Notch signaling stimulated SC proliferation in damaged adult utricles, priming these cells with the potential to regenerate sensory HCs. Subsequent inhibition of Notch signaling removed lateral inhibition barriers, promoting the transition from proliferating SCs to HCs. Our findings underscore the crucial role of Notch signaling in promoting vestibular HC regeneration.

Objective: This study aims to assess overall rates of neuroimaging (computed tomography [CT] or magnetic resonance imaging [MRI]) and cerebrovascular accidents (CVAs) in patients presenting to the emergency department (ED) with primary diagnoses of dizziness/vertigo to determine if neuroimaging is overused in this population.

Study Design: Population-based ED registry analysis.

Setting: 2020 Nationwide Emergency Department Sample.

Patients: Patients presenting to the ED with dizziness/vertigo.

Interventions: Rates of neuroimaging (both CT and MRI), common associated diagnoses and symptoms, and CVAs.

Main Outcome Measures: Odds ratio (OR) and multivariate analysis were performed on the associations of common ED diagnoses with admission and CVAs.

Results 1,115,826 ED presentations received a primary diagnosis of vertigo/dizziness, resulting in $8.4 billion in ED charges. Of the patients discharged from the ED, 42.29% underwent neuroimaging. Overall, 2046 (0.18%) patients had a diagnosis of CVA. 89.46% of vertigo/dizziness patients with a CVA had at least one of 24 risk factors, including diabetes, history of thromboembolic event, nystagmus, and others, that were significantly associated with the presence of CVA in multivariate analysis. Current procedural terminology (CPT) codes of H81.2 (vestibular neuronitis) and H81.4 (vertigo of central origin) were significantly associated with CVA when compared to other forms of dizziness/vertigo (adjusted ORs of 3.26 and 3.98; p < 0.001).

Conclusions A high proportion of ED patients with vertigo/dizziness undergo neuroimaging to rule out CVA, while only 0.18% are diagnosed with CVA. 24 diagnoses are positively associated with CVAs in patients presenting with vertigo/dizziness and can decrease neuroimaging rates and lower healthcare costs.

Purpose: The small and complex space of the intranasal cavity poses a challenge to teaching and learning sinonasal anatomy in undergraduate medical education. Evidence suggests that utilizing 3D-printed (3DP) models is an effective means to comprehend anatomical structures and their spatial relationships. In this study, we introduce and evaluate the educational value of rigid nasal endoscopy on realistic 3DP and silicone-cast sinus models as a method to teach medical students intranasal anatomy.

Methods: Twelve first-year medical students participated in an educational rigidnasal endoscopy workshop led by Otolaryngology PGY-2 residents and rhinology consultants. The workshop consisted of (1) an introductory PowerPoint on rigid nasal endoscopy and basic intranasal anatomy, (2) timed trials that tested students' ability to locate intranasal anatomical structures while scoping with a rigid endoscope, and (3) pre- and post-surveys.

Results Participants improved in their ability to locate each intranasal anatomical structure during the timed trials. Participants felt that rigid endoscopy of 3DP models was an effective method to learn intranasal anatomy compared to their traditional medical school anatomy course.

Conclusion The results of this study suggest that rigid nasal endoscopy of 3DP sinus models is a potentially high-value educational method for teaching intranasal anatomy to first-year medical students. Students enjoyed the opportunity to learn intranasal anatomy while practicing a clinically relevant procedure - rigid nasal endoscopy.