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Wyszukujesz frazę "liver fibrosis" wg kryterium: Temat


Wyświetlanie 1-4 z 4
Tytuł:
Neutrophil-lymphocyte ratio and mean platelet volume as predictive factors for liver fibrosis and steatosis in patients with chronic hepatitis B
Autorzy:
Pokora-Rodak, A.
Kiciak, S.
Tomasiewicz, K.
Powiązania:
https://bibliotekanauki.pl/articles/2081973.pdf
Data publikacji:
2018
Wydawca:
Instytut Medycyny Wsi
Tematy:
neutrophil-lymphocyte ratio
hepatitis B
liver fibrosis
liver steatosis
Opis:
Objective. Evaluation of the neutrophil-lymphocyte ratio and mean platelet volume as predictive factors for liver fibrosis and steatosis in HBV patients qualified for antiviral treatment. Materials and method. The study comprised 38 CHB patients who had commenced antiviral treatment, and 20 healthy volunteers who constituted the clinical control group. All patients had their blood count taken and underwent hepatic assessment using transient elastography with CAP (controlled attenuation parameter). Results. It was found that the mean hepatic fibrosis was 8.7 kPa (±8.8) and the mean liver steatosis – 286 db/m (±64). Mean NLR – 2.78(±1.1), whereas in the control group the mean NLR value was 1.64(±0.98). A negative linear correlation (r= -0.34; p=0.035) was found between liver fibrosis and the NLR value in the study group. No correlation was observed between hepatic steatosis and the NLR. Mean MPV – 12.6fl (±3.1), which was considerably higher in the CBH patients than in the control group. A positive correlation (r= 0.79, p= 0.001) was found between MPV and disease severity evaluated with transient elastography. Conclusions. The NLR and the MPV were significantly higher in the CHB patients than in the healthy volunteers. Both the NLR and the MPV can be treated as predictive factors for liver fibrosis in this group of patients.
Źródło:
Annals of Agricultural and Environmental Medicine; 2018, 25, 4; 690-692
1232-1966
Pojawia się w:
Annals of Agricultural and Environmental Medicine
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Hepatoprotective effects of Tribulus terrestris, Ashwagandha and N-acetylcysteine on liver fibrosis in carbon tetrachloride-induced rats
Autorzy:
Altay, Derya
Dogan, Yasar
Orhan, Cemal
Tuzcu, Mehmet
Sahin, Nurhan
Ozercan, Ibrahim
Sahin, Kazım
Powiązania:
https://bibliotekanauki.pl/articles/895409.pdf
Data publikacji:
2019-10-30
Wydawca:
Polskie Towarzystwo Farmaceutyczne
Tematy:
N-acetylcysteine
carbon tetrachloride
liver fibrosis
Ashwagandha
Tribulus terrestris
Opis:
Background and Aim: Fibrosis, which develops during the progression of liver damage, is the previous stage of cirrhosis. Carbon tetrachloride is one of the most commonly used hepatic toxins in experimental animal models of liver fibrosis. It was investigated the hepatoprotective effects of Tribulus terrestris, Ashwagandha and N-acetylcysteine in an experimental model of liver fibrosis induced by carbon tetrachloride in this study. Methods: Fifty Wistar rats were divided into five groups of 10 each, as follows: 1) control, 2) carbon tetrachloride, 3) carbon tetrachloride plus N-acetylcysteine, 4) carbon tetrachloride plus T. terrestris, and 5) carbon tetrachloride plus Ashwagandha group. At the end of 6 weeks, the rats were sacrificed, and serum and tissue samples were collected. Aspartate aminotransferase, alanine aminotransferase, gamma-glutamyl transpeptidase, malondialdehyde, NF-κB, collagen 1, nuclear factor erythroid-2-related factor 2, tumor necrosis factor-α were analyzed, and histopathological evaluation was performed. Results: There were no significant differences in serum aspartate aminotransferase and alanine aminotransferase levels of the N-acetylcysteine-treated group versus those in the T. terrestris- and Ashwagandha-treated groups (p>0.05). Liver malondialdehyde levels were lower in the N-acetylcysteine-, T. terrestris- and Ashwagandha-treated groups than in the carbon tetrachloride-administered group (p<0.001). There were differences between groups in NF-κB, collagen 1, nuclear factor erythroid-2-related factor 2 and tumor necrosis factor-α levels (p<0.05). Conclusions: In conclusion, T. terrestris, Ashwagandha and N-acetylcysteine had protective effects on the liver in this experimental fibrosis model. T.Terrestris was a little more effective than Ashwagandha in combating liver fibrosis.
Źródło:
Acta Poloniae Pharmaceutica - Drug Research; 2019, 76, 5; 805-813
0001-6837
2353-5288
Pojawia się w:
Acta Poloniae Pharmaceutica - Drug Research
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Simple and non-invasive liver fibrosis stage prediction method
Autorzy:
Orczyk, T.
Pałys, M.
Porwik, P.
Musialik, J.
Błońska-Fajfrowska, B.
Powiązania:
https://bibliotekanauki.pl/articles/333411.pdf
Data publikacji:
2011
Wydawca:
Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
Tematy:
zwłóknienie wątroby
wirusowe zapalenie wątroby typu C
przewidywanie etapu
liver fibrosis
hepatitis C
stage prediction
Opis:
In this paper a simple and non-expensive indirect fibrosis stage prediction method is described. Presented method is non-invasive and is based on the results of the generic blood tests. The method is based on a statistical analysis of wide range of blood tests results supported with the experience of hepatologists.
Źródło:
Journal of Medical Informatics & Technologies; 2011, 17; 227-231
1642-6037
Pojawia się w:
Journal of Medical Informatics & Technologies
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Classification techniques for non-invasive recognition of liver fibrosis stage
Autorzy:
Krawczyk, B.
Woźniak, M.
Orczyk, T.
Porwik, P.
Musialik, J.
Błońska-Fajfrowska, B.
Powiązania:
https://bibliotekanauki.pl/articles/332969.pdf
Data publikacji:
2012
Wydawca:
Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
Tematy:
uczenie maszynowe
systemy wielo-klasyfikatorów
informatyka medyczna
zwłóknienie wątroby
wirusowe zapalenie wątroby typu C
machine learning
multiple classifier systems
compound pattern recognition
medical informatics
liver fibrosis
hepatitis C
Opis:
Contemporary medicine should provide high quality diagnostic services while at the same time remaining as comfortable as possible for a patient. Therefore novel non-invasive disease recognition methods are becoming one of the key issues in the health services domain. Analysis of data from such examinations opens an interdisciplinary bridge between the medical research and artificial intelligence. The paper presents application of machine learning techniques to biomedical data coming from indirect examination method of the liver fibrosis stage. Presented approach is based on a common set of non-invasive blood test results. The performance of four different compound machine learning algorithms, namely Bagging, Boosting, Random Forest and Random Subspaces, is examined and grid search method is used to find the best setting of their parameters. Extensive experimental investigations, carried out on a dataset collected by authors, show that automatic methods achieve a satisfactory level of the fibrosis level recognition and may be used as a real-time medical decision support system for this task.
Źródło:
Journal of Medical Informatics & Technologies; 2012, 20; 121-127
1642-6037
Pojawia się w:
Journal of Medical Informatics & Technologies
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-4 z 4

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