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Summary: Background: The Cutaneous Lupus Erythematosus Disease Area and Severity Index (CLASI) is a reliable outcome measure for cutaneous lupus erythematosus (CLE) in adults used in clinical trials. However, it has not been validated in children, limiting clinical trials for paediatric CLE. Objectives: This study aimed to validate the CLASI in paediatrics. Methods: Eleven paediatric patients with CLE, six dermatologists and six rheumatologists participated. The physicians were trained to use the CLASI and Physician's Global Assessment (PGA), and individually rated all patients using both tools. Each physician reassessed two randomly selected patients. Within each physician group, the intraclass correlation coefficient (ICC) was calculated to assess the reliability of each measure. Results: CLASI activity scores demonstrated excellent inter‐ and intrarater reliability (ICC > 0·90), while the PGA activity scores had good inter‐rater reliability (ICC 0·73–0·77) among both specialties. PGA activity scores showed excellent (ICC 0·89) and good intrarater reliability (ICC 0·76) for dermatologists and rheumatologists, respectively. Limitations of this study include the small sample size of patients and potential recall bias during the physician rerating session. Conclusions: CLASI activity measurement showed excellent inter‐ and intrarater reliability in paediatric CLE and superiority over the PGA. These results demonstrate that the CLASI is a reliable and valid outcome instrument for paediatric CLE. What's already known about this topic? The Cutaneous Lupus Erythematosus Disease Area and Severity Index (CLASI) has been established as a reliable outcome measure for CLE in adults and is used in clinical trials. What does this study add? This study validates the reliability of the CLASI in the paediatric population with CLE, which can manifest differently from CLE in adults.This validation will allow clinical trials to assess treatment efficacy reliably in CLE. Linked Comment: Chong. Br J Dermatol 2019; 180:20–21. Plain language summary available online Respond to this article [ABSTRACT FROM AUTHOR]

A male patient in his 80s was brought to our emergency room with a one-day history of general malaise and cough. He had received a severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) vaccination seven days earlier. He initially presented with respiratory failure, and an alveolar hemorrhage was suspected. The patient was intubated and admitted to the intensive care unit. We suspected that the alveolar hemorrhage was caused by acute respiratory distress syndrome (ARDS). Treatment including high-dose corticosteroid therapy and venovenous extracorporeal membrane oxygenation (ECMO) was initiated, however, the patient did not respond to treatment and died 35 days after admission. Pathological autopsy revealed diffuse alveolar damage (DAD) and idiopathic diffuse alveolar hemorrhage (DAH) consistent with ARDS. ARDS should be considered as a differential diagnosis when a patient develops respiratory symptoms after receiving the SARS-CoV-2 vaccine., Competing Interests: Human subjects: Consent was obtained or waived by all participants in this study. Conflicts of interest: In compliance with the ICMJE uniform disclosure form, all authors declare the following: Payment/services info: All authors have declared that no financial support was received from any organization for the submitted work. Financial relationships: All authors have declared that they have no financial relationships at present or within the previous three years with any organizations that might have an interest in the submitted work. Other relationships: All authors have declared that there are no other relationships or activities that could appear to have influenced the submitted work., (Copyright © 2024, Kawano et al.)

Introduction: The tongue plays an important role in mastication, swallowing, and articulation, but it cannot be directly observed because of its location inside the oral cavity. This study aimed to clarify detailed 3D tongue movements during chewing using electromagnetic articulography (EMA)., Materials and Methods: The participants were 10 healthy, young volunteers (average age 26.8 ± 2.1 years; 5 males, 5 females). Tongue and jaw movement during gum chewing was measured and recorded using EMA. Four EMA sensors were attached to the anterior, posterior, left, and right surfaces of the tongue, and one sensor was also attached to the mandibular left incisor. The tongue motion during the chewing cycle was spatially and sequentially analyzed based on the motion trajectories of the tongue and mandible., Results and Discussion: The tongue moved downward and to the masticatory side in a manner similar to the movement of the jaw. The anterior tongue marker moved downward to a greater extent than the other tongue markers. However, the tongue moved forward as the jaw moved backward. The anterior marker reached the most anterior position during the jaw-opening phase and the posterior markers reached the most anterior position during the jaw-closing phase. Just before maximum jaw-opening, all markers on the tongue reached the bottom lowest position. During the jaw-closing phase, the tongue reached the dominant farthest position in the masticatory side. All the markers reached the most posterior position during the occlusal phase., Conclusion: These findings demonstrate the sequence of tongue motion patterns during gum chewing., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Sato, Kodama, Okawa, Murakami, Ono and Hori.)

Background: Coordination among lip, cheek and tongue movements during swallowing in patients with mandibular prognathism remains unclear., Objectives: This study aimed to identify the temporal sequences of tongue pressure and maxillofacial muscle activities during swallowing in patients with mandibular prognathism and compared characteristics with those of healthy volunteers., Methods: Seven patients with mandibular prognathism (mandibular prognathism group) and 25 healthy volunteers with individual normal occlusion (control group) were recruited. Tongue pressures and masseter, orbicularis oris, mentalis and supra- and infrahyoid muscle activities while swallowing gel were measured simultaneously using a sensor sheet system with five measurement points and surface electromyography, respectively. Onset time, offset time and durations of tongue pressure and muscle activities were analysed., Results: In the mandibular prognathism group, tongue pressure was often produced first in more peripheral parts of the palate. Offset of tongue pressure in the posteromedian and peripheral parts of the palate and maxillofacial muscle activities except for orbicularis oris were delayed. Duration of tongue pressure in the anteromedian part of the palate was significantly shorter and durations of masseter, mentalis and suprahyoid muscle activities were significantly longer. Times to onset of orbicularis oris and suprahyoid muscle activities based on first onset of tongue pressure were significantly shorter., Conclusion: These results suggest that patients with mandibular prognathism may exhibit specific patterns of tongue pressure production and maxillofacial muscle activities during swallowing., (© 2024 John Wiley & Sons Ltd.)

Purpose: To build an image recognition network to evaluate tongue coating status., Methods: Two image recognition networks were built: one for tongue detection and another for tongue coating classification. Digital tongue photographs were used to develop both networks; images from 251 (178 women, 74.7±6.6 years) and 144 older adults (83 women, 73.8±7.3 years) who volunteered to participate were used for the tongue detection network and coating classification network, respectively. The learning objective of the tongue detection network is to extract a rectangular region that includes the tongue. You-Only-Look-Once (YOLO) v2 was used as the detection network, and transfer learning was performed using ResNet-50. The accuracy was evaluated by calculating the intersection over the union. For tongue coating classification, the rectangular area including the tongue was divided into a grid of 7×7. Five experienced panelists scored the tongue coating in each area using one of five grades, and the tongue coating index (TCI) was calculated. Transfer learning for tongue coating grades was performed using ResNet-18, and the TCI was calculated. Agreement between the panelists and network for the tongue coating grades in each area and TCI was evaluated using the kappa coefficient and intraclass correlation, respectively., Results: The tongue detection network recognized the tongue with a high intersection over union (0.885±0.081). The tongue coating classification network showed high agreement with tongue coating grades and TCI, with a kappa coefficient of 0.826 and an intraclass correlation coefficient of 0.807, respectively., Conclusions: Image recognition enables simple and detailed assessment of tongue coating status.

Competing Interests: Conflicts of interest: no conflicts of interest to disclose.