[Study on the Flavonoids and Biological Activity of Rubus sachalinensis].

Objective: To study the chemical constituents and biological activity of Rubus sachalinensis. Methods: The compounds in the ethyl acetate and n-butanol fraction were isolated and purified by macroporous resin,Sephadex LH-20 column chromatography,and reverse-phase preparative HPLC. The structures were identified by various spectroscopic data such as 1D,2D-NMR,HRMS. Antioxidant,anti-inflammatory and cytotoxicity of the compounds were determined by FRAP,Griess and MTT methods. Results: Eight compounds were isolated from the ethyl acetate and n-butanol extract of Rubus sachalinensis,and identified as kaempferol-3-O-ß-D-butyl glucuronate( 1),quercetin-3-O-ß-D-butyl glucuronate( 2),quercetin-3-O-ß-D-glucopyranoside( 3),cis-tiliroside( 4),tiliroside( 5),quercetin-3-O-ß-D-ethyl glucuronate( 6),quercetin( 7) and kaempferol( 8). Activity assay showed that the compounds 1 ~ 8 had different levels of antioxidant activity,all the compounds showed cytotoxicities of IC50 greater than 200 µmol / L. Conclusion: Flavonoids are the main antioxidant consitituents of Rubus sachalinensis and have a good anti-inflammatory activity. All the compounds are isolated from this plant for the first time,compounds 1,2,6 are obtained from the this genus for the first time.

Machine Learning-Based Prediction of Complications and Prolonged Hospitalization with the GLIM Criteria Combinations Containing Calf Circumference in Elderly Asian Patients.

BACKGROUND AND AIMS: Malnutrition is widely present and influences the prognosis of elderly inpatients, so it is helpful to be able to identify it with a convenient method. However, in the widely accepted criteria for malnutrition, the Global Leadership Initiative on Malnutrition (GLIM), a lot of metrics can be used to define the phenotypic and etiological criteria. To identify muscle mass reduction, anthropometric parameters such as calf circumference (CC) and hand grip strength (HGS) are preferable to other expensive methods in many situations because they are easy and inexpensive to measure, but their applicability needs to be verified in specific clinical scenarios. This study aims to verify the value of CC- and HGS-identified muscle loss in diagnosing malnutrition and predicting in-hospital complications (IHC) and prolonged length of hospital stay (PLOS) in elderly inpatients using machine learning methods. METHODS: A sample of 7122 elderly inpatients who were enrolled in a previous multicenter cohort study in China were screened for eligibility for the current study and were then retrospectively diagnosed for malnutrition using 33 GLIM criteria that differ in their combinations of phenotypic and etiological criteria, in which CC or CC+HGS were used to identify muscle mass reduction. The diagnostic consistency with the subjective global assessment (SGA) criteria at admission was evaluated according to Kappa coefficients. The association and the predictive value of the GLIM-defined malnutrition with 30-day IHC and PLOS were evaluated with logistic regression and randomized forest models. RESULTS: In total, 2526 inpatients (average age 74.63 ± 7.12 years) were enrolled in the current study. The prevalence of malnutrition identified by the 33 criteria combinations ranged from 3.3% to 27.2%. The main IHCs was infectious complications (2.5%). The Kappa coefficients ranged from 0.130 to 0.866. Logistic regression revealed that malnutrition was identified by 31 GLIM criteria combinations that were significantly associated with 30-day IHC, and 22 were significantly associated with PLOS. Random forest prediction revealed that GLIM 15 (unconscious weight loss + muscle mass reduction, combined with disease burden/inflammation) performs best in predicting IHC; GLIM 30 (unconscious weight loss + muscle mass reduction + BMI reduction, combined with disease burden/inflammation) performs best in predicting PLOS. Importantly, CC alone performs better than CC+HGS in the criteria combinations for predicting adverse clinical outcomes. CONCLUSION: Muscle mass reduction defined by a reduced CC performs well in the GLIM criteria combinations for diagnosing malnutrition and predicting IHC and PLOS in elderly Asian inpatients. The applicability of other anthropometric parameters in these applications needs to be further explored.

Machine Learning-Based Prediction of In-Hospital Complications in Elderly Patients Using GLIM-, SGA-, and ESPEN 2015-Diagnosed Malnutrition as a Factor.

BACKGROUND: Malnutrition is prevalent in elderly inpatients and is associated with various adverse outcomes during their hospital stay, but the diagnosis of malnutrition still lacks widely applicable criteria. This study aimed to investigate the association of malnutrition diagnosed with the SGA, ESPEN 2015, and GLIM criteria, respectively, with in-hospital complications in elderly patients. METHOD: Hospitalized patients over 65 years old who had been assessed with the SGA guideline for malnutrition at admission were retrospectively recruited from a large observational cohort study conducted in 34 level-A tertiary hospitals in 18 cities in China from June to September 2014. Malnutrition was then retrospectively diagnosed using the GLIM and ESPEN 2015 criteria, respectively, for comparison with the results of the SGA scale. The risk factors for malnutrition were analyzed using logistic regression, and the value of the three diagnostic criteria in predicting the in-hospital complications was subsequently explored using multivariate regression and the random forest machine learning algorithm. RESULTS: A total of 2526 subjects who met the inclusion and exclusion criteria of the study were selected from the 7122 patients in the dataset, with an average age of 74.63 ± 7.12 years, 59.2% male, and 94.2% married. According to the GLIM, SGA, and ESPEN 2015 criteria, the detection rates of malnutrition were 37.8% (956 subjects), 32.8% (829 subjects), and 17.0% (429 subjects), respectively. The diagnostic consistency between the GLIM and the SGA criteria is better than that between the ESPEN 2015 and the SGA criteria (Kappa statistics, 0.890 vs. 0.590). Logistic regression showed that the risk of developing complications in the GLIM-defined malnutrition patients is 2.414 times higher than that of normal patients, higher than those of the ESPEN 2015 and SGA criteria (1.786 and 1.745 times, respectively). The random forest classifications show that the GLIM criteria have a higher ability to predict complications in these elderly patients than the SGA and ESPEN 2015 criteria with a mean decrease in accuracy of 12.929, 10.251, and 5.819, respectively, and a mean decrease in Gini of 2.055, 1.817, and 1.614, respectively. CONCLUSION: The prevalence of malnutrition diagnosed with the GLIM criteria is higher than that of the SGA and the ESPEN 2015 criteria. The GLIM criteria are better than the SGA and the ESPEN 2015 criteria for predicting in-hospital complications in elderly patients.

Hypouricemic effect of flaccidoside II in rodents.

To investigate the effect of flaccidoside II on the serum uric acid levels in hyperuricemic rodents. Both mice and rats were injected intraperitoneally with potassium oxonate to induce hyperuricemia. Different dosages of flaccidoside II were orally administrated to hyperuricemic and normal rodents for 7 days, respectively. Liver xanthine oxidase (XOD) activities in hyperuricemic mice were determined using the colorimetric method. Acute toxicity of flaccidoside II was also evaluated in mice. Allopurinol, as a positive control, was administered under the same treatment scheme. The results showed that flaccidoside II (32, 16 and 8 mg/kg) could significantly lower serum uric acid levels in hyperuricemic mice. Flaccidoside II (24, 12 and 6 mg/kg) could also markedly lower serum uric acid levels in hyperuricemic rats. However, unlike allopurinol, oral administration of flaccidoside II did not produce any observable hypouricemic effect in normal animals. Flaccidoside II at the dose of 32 mg/kg significantly suppressed XOD activities in the liver of hyperuricemic mice, while at doses of 16 and 8 mg/kg flaccidoside II did not show a significant effect on XOD activities. In addition, flaccidoside II (300 mg/kg) has no or less toxicity than allopurinol in mice. These findings demonstrate that flaccidoside II exhibits anti-hyperuricemic activity in hyperuricemic animals.