| 1. |
- Lindberg, Ann-Sofie, 1972-, et al.
(författare)
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Multivariate statistical assessment of predictors of firefighters' muscular and aerobic work capacity
- 2015
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Ingår i: PLOS ONE. - : Public Library of Science. - 1932-6203. ; 10:3
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Tidskriftsartikel (refereegranskat)abstract
- Physical capacity has previously been deemed important for firefighters physical work capacity, and aerobic fitness, muscular strength, and muscular endurance are the most frequently investigated parameters of importance. Traditionally, bivariate and multivariate linear regression statistics have been used to study relationships between physical capacities and work capacities among firefighters. An alternative way to handle datasets consisting of numerous correlated variables is to use multivariate projection analyses, such as Orthogonal Projection to Latent Structures. The first aim of the present study was to evaluate the prediction and predictive power of field and laboratory tests, respectively, on firefighters’ physical work capacity on selected work tasks. Also, to study if valid predictions could be achieved without anthropometric data. The second aim was to externally validate selected models. The third aim was to validate selected models on firefighters’ and on civilians’. A total of 38 (26 men and 12 women) + 90 (38 men and 52 women) subjects were included in the models and the external validation, respectively. The best prediction (R2) and predictive power (Q2) of Stairs, Pulling, Demolition, Terrain, and Rescue work capacities included field tests (R2 = 0.73 to 0.84, Q2 = 0.68 to 0.82). The best external validation was for Stairs work capacity (R2 = 0.80) and worst for Demolition work capacity (R2 = 0.40). In conclusion, field and laboratory tests could equally well predict physical work capacities for firefighting work tasks, and models excluding anthropometric data were valid. The predictive power was satisfactory for all included work tasks except Demolition.
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| 2. |
- Mörén, Lina, 1985-, et al.
(författare)
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Metabolomic screening of tumor tissue and serum in glioma patients reveals diagnostic and prognostic information
- 2015
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Ingår i: Metabolites. - : MDPI. - 2218-1989. ; 5:3, s. 502-520
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Tidskriftsartikel (refereegranskat)abstract
- Glioma grading and classification, today based on histological features, is not always easy to interpret and diagnosis partly relies on the personal experience of the neuropathologists. The most important feature of the classification is the aimed correlation between tumor grade and prognosis. However, in the clinical reality, large variations exist in the survival of patients concerning both glioblastomas and low-grade gliomas. Thus, there is a need for biomarkers for a more reliable classification of glioma tumors as well as for prognosis. We analyzed relative metabolite concentrations in serum samples from 96 fasting glioma patients and 81 corresponding tumor samples with different diagnosis (glioblastoma, oligodendroglioma) and grade (World Health Organization (WHO) grade II, III and IV) using gas chromatography-time of flight mass spectrometry (GC-TOFMS). The acquired data was analyzed and evaluated by pattern recognition based on chemometric bioinformatics tools. We detected feature patterns in the metabolomics data in both tumor and serum that distinguished glioblastomas from oligodendrogliomas (p(tumor) = 2.46 × 10(-8), p(serum) = 1.3 × 10(-5)) and oligodendroglioma grade II from oligodendroglioma grade III (p(tumor) = 0.01, p(serum) = 0.0008). Interestingly, we also found patterns in both tumor and serum with individual metabolite features that were both elevated and decreased in patients that lived long after being diagnosed with glioblastoma compared to those who died shortly after diagnosis (p(tum)(o)(r) = 0.006, p(serum) = 0.004; AUROCC(tumor) = 0.846 (0.647-1.000), AUROCC(serum) = 0.958 (0.870-1.000)). Metabolic patterns could also distinguish long and short survival in patients diagnosed with oligodendroglioma (p(tumor) = 0.01, p(serum) = 0.001; AUROCC(tumor) = 1 (1.000-1.000), AUROCC(serum) = 1 (1.000-1.000)). In summary, we found different metabolic feature patterns in tumor tissue and serum for glioma diagnosis, grade and survival, which indicates that, following further verification, metabolomic profiling of glioma tissue as well as serum may be a valuable tool in the search for latent biomarkers for future characterization of malignant glioma.
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| 3. |
- Ruhal, Rohit, et al.
(författare)
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A multivariate approach to correlate bacterial surface properties to biofilm formation by lipopolysaccharide mutants of Pseudomonas aeruginosa
- 2015
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Ingår i: Colloids and Surfaces B. - : Elsevier. - 0927-7765 .- 1873-4367. ; 127:0, s. 182-191
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Tidskriftsartikel (refereegranskat)abstract
- Abstract Bacterial biofilms are involved in various medical infections and for this reason it is of great importance to better understand the process of biofilm formation in order to eradicate or mitigate it. It is a very complex process and a large range of variables have been suggested to influence biofilm formation. However, their internal importance is still not well understood. In the present study, a range of surface properties of Pseudomonas aeruginosa lipopolysaccharide mutants were studied in relation to biofilm formation measured in different kinds of multi-well plates and growth conditions in order to better understand the complexity of biofilm formation. Multivariate analysis was used to simultaneously evaluate the role of a range of physiochemical parameters under different conditions. Our results suggest the presence of serum inhibited biofilm formation due to changes in twitching motility. From the multivariate analysis it was observed that the most important parameters, positively correlated to biofilm formation on two types of plates, were high hydrophobicity, near neutral zeta potential and motility. Negative correlation was observed with cell aggregation, as well as formation of outer membrane vesicles and exopolysaccharides. This work shows that the complexity of biofilm formation can be better understood using a multivariate approach that can interpret and rank the importance of different factors being present simultaneously under several different environmental conditions, enabling a better understanding of this complex process.
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| 4. |
- Sjöberg, Rickard L., et al.
(författare)
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Blood Metabolomic Predictors of 1-Year Outcome in Subarachnoid Hemorrhage
- 2015
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Ingår i: Neurocritical Care. - : Springer. - 1541-6933 .- 1556-0961. ; 23:2, s. 225-232
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Tidskriftsartikel (refereegranskat)abstract
- Delayed neurological deficit (DND) is the most important cause of morbidity and mortality in patients with subarachnoid hemorrhage (SAH) whose aneurysms have been secured. However, the methods currently used to predict the development of DND, such as trans-cranial Doppler or levels biochemical markers in blood and cerebrospinal fluid are not very accurate. Venous blood was drawn from 50 patients with SAH, admitted to the neurosurgical department UmeAyen University Hospital, at day 1-3 and day 7 after the bleed. The clinical status of the patients was followed up approximately 1 year after this episode and classified according to the Glasgow Outcome Score (GOS). Results showed considerable differences in blood metabolomic patterns between day 1-3 and 7 after the hemorrhage. Fifty-six out of 98 metabolites could be identified from our in-house library and 17 of these metabolites changed significantly from day 1-3 to 7 after the bleed. One of these, myo-inositol, was predictive of clinical outcome even after correction for multiple testing. An estimation of the diagnostic accuracy of high levels of this substance in predicting good outcome (GOS 4-5) yielded a sensitivity of .763 and a specificity of .5 at the optimal cut off point. SAH is an event with a profound effect on blood metabolomics profiles. Myo-inositol might be an interesting compound for future study to focus on in the search for metabolic markers in venous blood of delayed neurological deterioration in SAH patients.
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