Diseases not only manifest as internal structural and functional abnormalities, but also have facial characteristics and appearance deformities. Specific facial phenotypes are potential diagnostic markers, especially for endocrine and metabolic syndromes, genetic disorders, facial neuromuscular diseases, etc. The technology of facial recognition (FR) has been developed for more than a half century, but research in automated identification applied in clinical medicine has exploded only in the last decade. Artificial-intelligence-based FR has been found to have superior performance in diagnosis of diseases. This interdisciplinary field is promising for the optimization of the screening and diagnosis process and assisting in clinical evaluation and decision-making. However, only a few instances have been translated to practical use, and there is need of an overview for integration and future perspectives. This review mainly focuses on the leading edge of technology and applications in varieties of disease, and discusses implications for further exploration.

The prereceptor activation of glucocorticoid production in adipose tissue by NADPH-dependent 11β-hydroxysteroid dehydrogenase type 1 (11β-HSD1) has emerged as a potential mechanism in the pathogenesis of visceral obesity and metabolic syndrome. Hexose-6-phosphate dehydrogenase (H6PDH) is an endoplasmic reticulum lumen-resident enzyme that generates cofactor NADPH and thus mediates 11β-HSD1 activity. To determine the role of adipose H6PDH in the prereceptor modulation of 11β-HSD1 and metabolic phenotypes, we generated a transgenic (Tg) mouse model overexpressing H6PDH under the control of the enhancer-promoter region of the adipocyte fatty acid-binding protein (aP2) gene (aP2/H6PDH Tg mice). Transgenic aP2/H6PDH mice exhibited relatively high expression of H6PDH and elevated corticosterone production with induction of 11β-HSD1 activity in adipose tissue. This increase in corticosterone production in aP2-H6PDH Tg mice resulted in mild abdominal fat accumulation with induction of C/EBP mRNA expression and slight weight gain. Transgenic aP2/H6PDH mice also exhibited fasting hyperglycemia and glucose intolerance with insulin resistance. In addition, the aP2/H6PDH Tg mice have elevated circulating free fatty acid levels with a concomitant increased adipose lipolytic action associated with elevated HSL mRNA and Ser⁶⁶⁰HSL phosphorylation within abdominal fat. These results suggest that increased H6PDH expression specifically in adipose tissue is sufficient to cause intra-adipose glucocorticoid production and adverse metabolic phenotypes. These findings suggest that the aP2/H6PDH Tg mice may provide a favorable model for studying the potential impact of H6PDH in the pathogenesis of human metabolic syndrome.

Background: Sodium fluctuation is independently associated with clinical deterioration. We developed and validated a prognostic index based on sodium fluctuation for risk stratification and in-hospital monitoring. Methods: This study included 33,323 adult patients hospitalized at a tertiary care hospital in 2014. The first 28,279 hospitalizations were analyzed to develop the model and then the validity of the model was tested using data from 5044 subsequent hospitalizations. We predict in-hospital mortality using age, comorbidity, range of sodium fluctuation, and duration of sodium fluctuation, abbreviated as CARDS. Results: In-hospital mortality was similar in the derivation (0.6%) and validation (0.4%) cohorts. In the derivation cohort, four independent risk factors for mortality were identified using logistic regression: age (66–75, 2 points; >75, 3 points); Charlson comorbidity index (>2, 5 points); range of sodium fluctuation (7–10, 4 points; >10, 10 points); and duration of fluctuation (≤3, 3 points). The AUC was 0.907 (95% CI: 0.885–0.928) in the derivation cohort and 0.932 (95% CI: 0.895–0.970) in the validation cohort. In the derivation cohort, in-hospital mortality was 0.106% in the low-risk group (0–7 points), 1.076% in the intermediate-risk group (8–14 points), and 8.463% in the high-risk group (15–21 points). In the validation cohort, in-hospital mortality was 0.049% in the low-risk group, 1.064% in the intermediate-risk group, and 8.403% in the high-risk group. Conclusions: These results suggest that patients at low, intermediate, and high risk for in-hospital mortality may be identified by CARDS mainly based on sodium fluctuation.

Background: The triglyceride-glucose (TyG) index has demonstrated promising predictive capability in clinical studies, but its distribution characteristics across different age and sex groups in the Chinese population have not been fully characterized. Objective: This study aimed to describe the population-based distribution of the TyG index. Methods: A total of 4621 participants aged 20‐80 years from the China National Health Survey were included in this study. The TyG index was calculated from fasting blood glucose and triglycerides. The age- and sex-specific distribution values of the TyG index were obtained using the percentiles method. Results: Males had higher BMI (23.32, SD 2.63 vs 22.72, SD 2.60 kg/m ² ), triglyceride (133.78, SD 78.07 vs 111.58, SD 61.18 mg/dL), fasting glucose (97.05, SD 11.95 vs 94.34, SD 10.46 mg/dL), and TyG index values (8.63, SD 0.54 vs 8.45, SD 0.50) than females. The TyG index of males reached its peak value at approximately 40 years of age. The lower limit percentile values for females exceeded that of males around age 50. After the age of 60, the upper limit of the distribution values in females was higher than in males. Conclusions: This study characterized the age- and sex-specific distribution of the TyG index among Chinese adults aged 20‐80 years. The results of this study contribute to a more precise assessment of glucolipid metabolism.