Chemical Composition of Essential Oil from Flower Heads of Arnica Chamissonis Less. under a Nitrogen Impact.

Chamisso arnica (Arnica chamissonis Less.) is a valuable plant species used in the pharmaceutical industry due to the content of many pharmacologically active substances and the similarity of its chemical composition to that of Arnica montana-a medicinal plant commonly used in pharmacy and cosmetics. The similarity of the two plant species implies that chamisso arnica can be a pharmaceutical substitute for the mountain arnica, i.e., an endangered and endemic plant species in Europe. Chamisso arnica extracts exhibit anti-inflammatory and antiradical activity and possesses high antioxidant properties that might be helpful in preventing or delaying the progress of free radical dependent diseases. The attributes of A. chamissonis are mainly related to the content and chemical composition of essential oil. Therefore, the objective of this study was to characterize the chemical composition of essential oil derived from A. chamissonis flower heads under a nitrogen impact. The experiment was performed on experimental fields in mid-eastern Poland on two soil types (sandy and loamy soils). The nitrogen fertilizer was applied as ammonium sulfate (control, 30, 60, 90, and 120 kg N ha-1). Collection of flower heads was carried out in the full flowering phase, which was characterized by the highest content of essential oil. The chemical composition of essential oil was examined using GC-MS. Among the 75 ingredients of the volatile oil of chamisso arnica flower heads, alpha-pinene, cumene, p-cymene, germacrene D, spathulenol, decanal, caryophyllene oxide, beta-pinene, and benzene acetaldehyde were present at relatively high levels. Both the nitrogen application and the soil type had an effect on the oil concentration and the yield of the main constituents (alpha-pinene and germacrene D) with pharmacological value. Different levels of nitrogen application could be considered as a relevant way to modify the chemical composition and to increase the essential oil production.

Prediction of severe retinopathy of prematurity using the WINROP algorithm in a cohort from Malopolska. A retrospective, single-center study.

INTRODUCTION: Retinopathy of prematurity (ROP) is one of the leading avoidable causes of blindness in childhood in developed countries. Accurate diagnosis and treatment are essential for preventing the loss of vision. WINROP (https://www.winrop.com) is an online monitoring system which predicts the risk for ROP requiring treatment based on gestational age, birth weight, and body weight gain. AIM: To validate diagnostic accuracy of the WINROP algorithm for the detection of severe ROP in a single centre cohort of Polish, high-risk preterm infant population. MATERIAL AND METHODS: Medical records of neonates born before 32 weeks of gestation admitted to the third level neonatal centre in a 2-year retrospective investigation 79 patients were included in the study: their gestational age, birth weight and body weight gain were set in the WINROP system. The algorithm evaluated the risk for ROP divided into low or high-risk of disease and identified infants with high risk of developing severe ROP (type 1 ROP). RESULTS: Out of 79 patients 37 received a high-risk alarm, of whom 22 developed severe ROP. Low-risk alarm was triggered in 42 infants; five of them developed type 1 ROP. The sensitivity of the WINROP was found to be 81.5% (95% CI 61.9-93.7), specificity 71.2% (95% CI 56.9-82.9), negative predictive value (NPV) 88.1% (95% CI 76.7-94.3), and positive predictive value (PPV) 59.5 (95% CI 48.1-69.9), respectively. The accuracy of the test significantly increased after combined WINROP and surfactant therapy as an additional factor - sensitivity 96.3% (95% CI 81.0-99.9), specificity 63.5% (95% CI 49.0-76.4), NPV 97.1% (95% CI 82.3-99.6), and PPV 57.8 (95% CI 48.7-66.4). CONCLUSIONS: The WINROP algorithm sensitivity from the Polish cohort was not as high as that reported in developed countries. However, combined with additional factors (e.g. surfactant treatment) it can be useful for identifying the risk groups of sight-threatening ROP. The accuracy of the WINROP algorithm should be validated in a large multi-center prospective study in a Polish population of preterm infants.