Deep learning-based histopathological assessment of tubulo-interstitial injury in chronic kidney diseases.

Background: Chronic kidney disease (CKD) causes progressive and irreversible damage to the kidneys. Renal biopsies are essential for diagnosing the etiology and prognosis of CKD, while accurate quantification of tubulo-interstitial injuries from whole slide images (WSIs) of renal biopsy specimens is challenging with visual inspection alone.

Methods: We develop a deep learning-based method named DLRS to quantify interstitial fibrosis and inflammatory cell infiltration as tubulo-interstitial injury scores, from WSIs of renal biopsy specimens.

Efficacy of corneal squamous cell carcinoma antigen-1 in early infancy in predicting atopic dermatitis and food allergy: A prospective study.

Background: Identification of predictive biomarkers is crucial for formulating preventive interventions and halting the progression of atopic march. Although controversial, the use of accessible markers to predict or detect early onset of atopic diseases is highly desirable. Therefore, this study aimed to investigate whether corneal squamous cell carcinoma antigen-1 (SCCA1) collected from infants can predict the development of atopic dermatitis and food allergy.

The Change of Asymptomatic Atlantoaxial Instability With Down Syndrome From Infant to Adolescent in Japanese Population: Minimum 10 Years Follow-Up.

Background: Although 10% to 60% of patients with Down syndrome (DS) develop atlantoaxial instability (AAI), clarifying the course of asymptomatic AAI may prevent unnecessary clinical interactions and investigations. This study investigates the radiographic changes observed in asymptomatic AAI associated with DS in Japanese children as they grow from infancy to adolescence over a minimum of 10 years.

Methods: A retrospective analysis of cervical radiographs acquired from asymptomatic patients with DS in both infancy and adolescence was carried out.

Borderline Range Determined Using Data From Validation Study of Alternative Methods for Skin Sensitization: ADRA, IL-8 Luc Assay, and EpiSensA.

Most predictive models that use alternatives to animal experiments divide judgements into two classes with a cutoff value for each model. However, if the results of alternative methods are close to the cutoff values, the true result may be ambiguous because of variability in the data. Therefore, the OECD GL497 uses a judgement method that establishes a borderline range (BR) around a cutoff value using a statistical method.

Skin health survey on atopic dermatitis among Japanese children: The Tohoku Medical Megabank Project Birth and Three-Generation Cohort Study.

Background: Precise skin phenotypic data are indispensable in accurately diagnosing atopic dermatitis (AD). Therefore, this study examined the interobserver concordance for AD and non-AD diagnoses between two dermatologists. AD prevalence determined by the self-reported physician diagnoses and the diagnoses determined from the United Kingdom (UK) diagnostic criteria were compared with the diagnoses made by the two dermatologists, using data from a skin health survey.