Gene/Protein Disease Symptom Drug Enzyme Compound
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Query: UMLS:C0015672 (fatigue)
 51,768 document(s) hit in 31,850,051 MEDLINE articles (0.00 seconds)

One hundred and two dentate patients with type II diabetes mellitus and 98 non-diabetic subjects were examined for oral conditions and metabolic state. Self-reported health behaviour was analysed. From factor analysis four factors emerged: general health behaviour (GHB), perceived fatigue (PF), diet control (DC) and regular diet (RD). In diabetics PF, DC and RD were significantly higher than that in non-diabetics. Patients with diabetes were more likely to control their disease through a programme of decreased kilojoule intake leading to weight management. However, they tended to tire. The mean gingivitis index was significantly higher (p < 0.01) among diabetics (2.39) than among non-diabetics (1.99). The number of missing teeth was significantly higher (p < 0.01) for diabetics (6.7) when compared with non-diabetics (4.3). On the other hand, aetiological factors (plaque, calculus) and the level of dental health behaviour as expressed in the HU-DBI scores were similar. Probing pocket depth did not differ statistically between groups. The increasing number of missing teeth in diabetics may primarily result from severe periodontitis with tooth mobility or deep pockets. Findings in this study suggest that the difference in the severity of periodontitis between diabetics and non-diabetics was significant although aetiological factors and the level of dental health behaviour were similar.
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PMID:Comparison of health behaviour and oral/medical conditions in non-insulin-dependent (type II) diabetics and non-diabetics. 984 81

Chronic fatigue syndrome (CFS) is a clinically defined condition characterized by long-lasting disabling fatigue. Because of the unknown mechanism underlying this syndrome, there still is no specific biomarker for objective assessment of the pathological fatigue. We have compared gene expression profiles in peripheral blood between 11 drug-free patients with CFS and age- and sex-matched healthy subjects using a custom microarray carrying complementary DNA probes for 1,467 stress-responsive genes. We identified 12 genes whose mRNA levels were changed significantly in CFS patients. Of these 12 genes, quantitative real-time PCR validated the changes in 9 genes encoding granzyme in activated T or natural killer cells (GZMA), energy regulators (ATP5J2, COX5B, and DBI), proteasome subunits (PSMA3 and PSMA4), putative protein kinase c inhibitor (HINT ), GTPase (ARHC), and signal transducers and activators of transcription 5A (STAT5A). Next, we performed the same microarray analysis on 3 additional CFS patients and 20 other patients with the chief complaint of long-lasting fatigue related to other disorders (non-CFS patients) and found that the relative mRNA expression of 9 genes classified 79% (11/14) of CFS and 85% (17/20) of the non-CFS patients. Finally, real-time PCR measurements of the levels of the 9 involved mRNAs were done in another group of 18 CFS and 12 non-CFS patients. The expression pattern correctly classified 94% (17/18) of CFS and 92% (11/12) of non-CFS patients. Our results suggest that the defined gene cluster (9 genes) may be useful for detecting pathological responses in CFS patients and for differential diagnosis of this syndrome.
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PMID:Identification of marker genes for differential diagnosis of chronic fatigue syndrome. 1859 70