Developing and validating clinical models to identify candidates for allergic rhinitis pre-exposure prophylaxis.

PURPOSE: Few risk-forecasting models of allergic rhinitis (AR) exist that may aid AR pre-exposure prophylaxis (PrEP) in clinical practice. Therefore, this study aimed to develop and validate an effective clinical model for identifying candidates for AR PrEP using a routine medical questionnaire. METHODS: This study was conducted in 10 Chinese provinces with 13 medical centers (n = 877) between 2019 and 2021. Clinical characteristics and exposure history were collected via face-to-face interviews. Well-trained physicians diagnosed patients with AR based on skin prick test results and clinical performance. The least absolute shrinkage and selection operator model was used to identify potential risk factors for AR, and the logistic regression model was used to construct the risk-forecasting model. Predictive power and model reliability were assessed using area under the receiver operating characteristic curve and calibration curves, respectively. RESULTS: This study diagnosed 625 patients with AR who had positive responses to at least one indoor or outdoor allergen and 460 to at least one outdoor pollen allergen. Two nomograms were established to identify two types of AR with various sensitization patterns. Both models had an area under curve of approximately 0.7 in the development and internal validation datasets. Additionally, our findings found good agreement for the calibration curves of both models. CONCLUSION: Early identification of candidates for AR PrEP using routine medical information may improve the deployment of limited resources and effective health management. Our models showed good performance in predicting AR; therefore, they can serve as potential automatic screening tools to identify AR PrEP candidates.

Patterns of aeroallergen sensitization in asthma patients identified by latent class analysis: A cross-sectional study in China.

BACKGROUND: This cross-sectional study aimed to identify latent sensitization profiles of asthma patients in mainland China, unveiling the association between regional differences and sensitization patterns. METHODS: 1056 asthma participants from 10 medical centers divided into eastern and western cohorts were clustered into four individual sensitization patterns, respectively, by using an unsupervised statistical modeling method, latent class analysis (LCA), based on the levels of 12 aeroallergens specific IgE reactivities. Moreover, differences in clinical characteristics and environmental exposures were compared in different sensitization patterns. RESULTS: Four distinct sensitization patterns in the two cohorts were defined as follows, respectively. Eastern cohort: Class 1: "High weed pollen and house dust mites (HDMs) sensitization" (8.87%), Class 2: "HDMs dominated sensitization" (38.38%), Class 3: "High HDMs and animal dander sensitization" (6.95%), Class 4: "Low/no aeroallergen sensitization" (45.80%). Western cohort: Class 1: "High weed pollen sensitization" (26.14%), Class 2: "High multi-pollen sensitization" (15.02%), Class 3: "HDMs-dominated sensitization" (10.33%), Class 4: "Low/no aeroallergen sensitization" (48.51%). Of note, the significant statistical difference in age, asthma control test score (ACT) and comorbidities were observed within or between different sensitization patterns. Exposure factors in different sensitization patterns were pointed out. CONCLUSIONS: Asthmatic patients with distinct sensitization patterns were clustered and identified through the LCA method, disclosing the relationship between sensitization profiles of multiple aeroallergens and geographical differences, providing novel insights and potential strategies for atopic disease monitoring, management and prevention in clinical practice.

An R2R3-MYB Transcription Factor OsMYBAS1 Promotes Seed Germination under Different Sowing Depths in Transgenic Rice.

MYB-type transcription factors play essential regulatory roles in seed germination and the response to seedling establishment stress. This study isolated a rice R2R3-MYB gene, OsMYBAS1, and functionally characterized its role in seed germination by generating transgenic rice plants with the overexpression and knockout of OsMYBAS1. Gene expression analysis suggested that OsMYBAS1 was highly expressed in brown rice and root, respectively. Subcellular localization analysis determined that OsMYBAS1 was localized in the nucleus. No significant differences in seed germination rate were observed among wild-type (WT) and transgenic rice plants at the 0-cm sowing depth. However, when sown at a depth of 4 cm, higher germination rates, root lengths and seedling heights were obtained in OsMYBAS1-overexpressing plants than in WT. Furthermore, the opposite results were recorded between the osmybas1 mutants and WT. Moreover, OsMYBAS1-overexpressing plants significantly enhanced superoxide dismutase (SOD) enzyme activity and suppressed the accumulation of malondialdehyde (MDA) content at the 4-cm sowing depth. These results indicate that the MYB transcription factor OsMYBAS1 may promote rice seed germination and subsequent seedling establishment under deep-sowing conditions. These findings can provide valuable insight into rice seed-quality breeding to facilitate the development of a dry, direct-seeding production system.

[Application of Fourier transform profilometry in 3D-surface reconstruction].

With the improvement of system frame and reconstruction methods in fluorescent molecules tomography (FMT), the FMT technology has been widely used as an important experimental tool in biomedical research. It is necessary to get the 3D-surface profile of the experimental object as the boundary constraints of FMT reconstruction algorithms. We proposed a new 3D-surface reconstruction method based on Fourier transform profilometry (FTP) method under the blue-purple light condition. The slice images were reconstructed using proper image processing methods, frequency spectrum analysis and filtering. The results of experiment showed that the method properly reconstructed the 3D-surface of objects and has the mm-level accuracy. Compared to other methods, this one is simple and fast. Besides its well-reconstructed, the proposed method could help monitor the behavior of the object during the experiment to ensure the correspondence of the imaging process. Furthermore, the method chooses blue-purple light section as its light source to avoid the interference towards fluorescence imaging.