Quantitative maps of rotating frame relaxation (RFR) time constants are sensitive and useful magnetic resonance imaging tools with which to evaluate tissue integrity in vivo. However, to date, only moderate image resolutions of 1.6 x 1.6 x 3.6 mm3 have been used for whole-brain coverage RFR mapping in humans at 3 T. For more precise morphometrical examinations, higher spatial resolutions are desirable. Towards achieving the long-term goal of increasing the spatial resolution of RFR mapping without increasing scan times, we explore the use of the recently introduced Transform domain NOise Reduction with DIstribution Corrected principal component analysis (T-NORDIC) algorithm for thermal noise reduction. RFR acquisitions at 3 T were obtained from eight healthy participants (seven males and one female) aged 52 ± 20 years, including adiabatic T1ρ, T2ρ, and nonadiabatic Relaxation Along a Fictitious Field (RAFF) in the rotating frame of rank n = 4 (RAFF4) with both 1.6 x 1.6 x 3.6 mm3 and 1.25 x 1.25 x 2 mm3 image resolutions. We compared RFR values and their confidence intervals (CIs) obtained from fitting the denoised versus nondenoised images, at both voxel and regional levels separately for each resolution and RFR metric. The comparison of metrics obtained from denoised versus nondenoised images was performed with a two-sample paired t-test and statistical significance was set at p less than 0.05 after Bonferroni correction for multiple comparisons. The use of T-NORDIC on the RFR images prior to the fitting procedure decreases the uncertainty of parameter estimation (lower CIs) at both spatial resolutions. The effect was particularly prominent at high-spatial resolution for RAFF4. Moreover, T-NORDIC did not degrade map quality, and it had minimal impact on the RFR values. Denoising RFR images with T-NORDIC improves parameter estimation while preserving the image quality and accuracy of all RFR maps, ultimately enabling high-resolution RFR mapping in scan times that are suitable for clinical settings.

• MeSH
• algoritmy MeSH
• analýza hlavních komponent MeSH
• dospělí MeSH
• lidé středního věku MeSH
• lidé MeSH
• magnetická rezonanční tomografie * metody   MeSH
• mapování mozku MeSH
• mozek * diagnostické zobrazování   MeSH
• poměr signál - šum * MeSH
• rotace MeSH
• senioři MeSH
• Check Tag
• dospělí MeSH
• lidé středního věku MeSH
• lidé MeSH
• mužské pohlaví MeSH
• senioři MeSH
• ženské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH

Multivariate techniques better fit the anatomy of complex neuropsychiatric disorders which are characterized not by alterations in a single region, but rather by variations across distributed brain networks. Here, we used principal component analysis (PCA) to identify patterns of covariance across brain regions and relate them to clinical and demographic variables in a large generalizable dataset of individuals with bipolar disorders and controls. We then compared performance of PCA and clustering on identical sample to identify which methodology was better in capturing links between brain and clinical measures. Using data from the ENIGMA-BD working group, we investigated T1-weighted structural MRI data from 2436 participants with BD and healthy controls, and applied PCA to cortical thickness and surface area measures. We then studied the association of principal components with clinical and demographic variables using mixed regression models. We compared the PCA model with our prior clustering analyses of the same data and also tested it in a replication sample of 327 participants with BD or schizophrenia and healthy controls. The first principal component, which indexed a greater cortical thickness across all 68 cortical regions, was negatively associated with BD, BMI, antipsychotic medications, and age and was positively associated with Li treatment. PCA demonstrated superior goodness of fit to clustering when predicting diagnosis and BMI. Moreover, applying the PCA model to the replication sample yielded significant differences in cortical thickness between healthy controls and individuals with BD or schizophrenia. Cortical thickness in the same widespread regional network as determined by PCA was negatively associated with different clinical and demographic variables, including diagnosis, age, BMI, and treatment with antipsychotic medications or lithium. PCA outperformed clustering and provided an easy-to-use and interpret method to study multivariate associations between brain structure and system-level variables. PRACTITIONER POINTS: In this study of 2770 Individuals, we confirmed that cortical thickness in widespread regional networks as determined by principal component analysis (PCA) was negatively associated with relevant clinical and demographic variables, including diagnosis, age, BMI, and treatment with antipsychotic medications or lithium. Significant associations of many different system-level variables with the same brain network suggest a lack of one-to-one mapping of individual clinical and demographic factors to specific patterns of brain changes. PCA outperformed clustering analysis in the same data set when predicting group or BMI, providing a superior method for studying multivariate associations between brain structure and system-level variables.

• MeSH
• analýza hlavních komponent * MeSH
• bipolární porucha * diagnostické zobrazování   farmakoterapie   patologie   MeSH
• dospělí MeSH
• lidé středního věku MeSH
• lidé MeSH
• magnetická rezonanční tomografie * metody   MeSH
• mladý dospělý MeSH
• mozek diagnostické zobrazování   patologie   MeSH
• mozková kůra diagnostické zobrazování   patologie   MeSH
• obezita * diagnostické zobrazování   MeSH
• schizofrenie diagnostické zobrazování   patologie   farmakoterapie   patofyziologie   MeSH
• shluková analýza MeSH
• Check Tag
• dospělí MeSH
• lidé středního věku MeSH
• lidé MeSH
• mladý dospělý MeSH
• mužské pohlaví MeSH
• ženské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH

Hepatocellular carcinoma (HCC) is one of the leading causes of cancer-related deaths in the world. HCC is often diagnosed late because patients with early-stage cancer have no apparent symptoms. Therefore, it is desirable to find a reliable method for an early diagnosis based on the detection of metabolites - biomarkers, that can be detected in the early stages of the disease. Untargeted metabolomics is often used as a tool to find a suitable biomarker for several diseases. In this work, untargeted metabolomics was performed on blood plasma samples of HCC patients and compared with healthy individuals and patients with liver cirrhosis. A combination of liquid chromatography and high-resolution mass spectrometry was used as an analytical method. More than a thousand peaks were detected in the blood plasma samples, from which mainly amino acids, carboxylic acids, lipids, and their derivatives were evaluated as potential biomarkers. The data obtained were statistically processed using the analysis of variance, correlation analysis, and principal component analysis.

• MeSH
• analýza hlavních komponent MeSH
• chromatografie kapalinová metody   MeSH
• dospělí MeSH
• hepatocelulární karcinom * krev   MeSH
• hmotnostní spektrometrie metody   MeSH
• jaterní cirhóza krev   diagnóza   MeSH
• lidé středního věku MeSH
• lidé MeSH
• metabolomika * metody   MeSH
• nádorové biomarkery * krev   MeSH
• nádory jater * krev   MeSH
• senioři MeSH
• studie případů a kontrol MeSH
• Check Tag
• dospělí MeSH
• lidé středního věku MeSH
• lidé MeSH
• mužské pohlaví MeSH
• senioři MeSH
• ženské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH

Wall paintings are integral to cultural heritage and offer rich insights into historical and religious beliefs. There exist various wall painting techniques that pose challenges in binder and pigment identification, especially in the case of egg/oil-based binders. GC-MS identification of lipidic binders relies routinely on parameters like the ratios of fatty acids within the plaster. However, the reliability of these ratios for binder identification is severely limited, as demonstrated in this manuscript. Therefore, a more reliable tool for effective differentiation between egg and oil binders based on a combination of diagnostic values, specific markers (cholesterol oxidation products), and PCA is presented in this study. Reference samples of wall paintings with egg and linseed oil binders with six different pigments were subjected to modern artificial ageing methods and subsequently analysed using two GC-MS instruments. A statistically significant difference (at a 95% confidence level) between the egg and oil binders and between the results from two GC-MS instruments was observed. These discrepancies between the results from the two GC-MS instruments are likely attributed to the heterogeneity of the samples with egg and oil binders. This study highlights the complexities in identifying wall painting binders and the need for innovative and revised analytical methods in conservation efforts.

• MeSH
• analýza hlavních komponent MeSH
• mastné kyseliny * MeSH
• plynová chromatografie s hmotnostně spektrometrickou detekcí MeSH
• reprodukovatelnost výsledků MeSH
• Publikační typ
• časopisecké články MeSH

Contemporary descriptions of motor control suggest that variability in movement can be indicative of skilled or unskilled performance. Here we used principal component analysis to study the kicking performance of elite and sub-elite soldiers who were highly familiar with the skill in order to compare the variability in the first and second principal components. The subjects kicked a force plate under a range of loaded conditions, and their movement was recorded using optical motion capture. The first principal component explained >92% of the variability across all kinematic variables when analyzed separately for each condition, and both groups and explained more of the variation in the movement of the elite group. There was more variation in the loading coefficient of the first principal component for the sub-elite group. In contrast, for the second principal component, there was more variation in the loading coefficient for the elite group, and the relative magnitude of the variation was greater than for the first principal component for both groups. These results suggest that the first principal component represented the most fundamental movement pattern, and there was less variation in this mode for the elite group. In addition, more of the variability was explained by the hip than the knee angle entered when both variables were entered into the same PCA, which suggests that the movement is driven by the hip.

• MeSH
• analýza hlavních komponent MeSH
• biomechanika MeSH
• dolní končetina * MeSH
• lidé MeSH
• pohyb * MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH

Lung cancer (LC) is the second most common malignancy and leading cause of cancer death. The potential "culprit" for local and systemic telomere shortening in LC patients is oxidative stress. We investigated the correlation between the peripheral blood leukocyte (PBL) telomere length (TL) and the presence/severity of LC and oxidative stress, and its usefulness as LC diagnostic marker. PBL TL was measured in 89 LC patients and 83 healthy subjects using the modified Cawthon RTq-PCR method. The relative PBL TL, found to be a potential diagnostic marker for LC with very good accuracy (P < 0.001), was significantly shorter in patients compared to the control group (CG) (P < 0.001). Significantly shorter telomeres were found in patients with LC TNM stage IV than in patients with stages I-III (P = 0.014), in patients without therapy compared to those on therapy (P = 0.008), and in patients with partial response and stable/progressive disease compared to those with complete response (P = 0.039). The total oxidant status (TOS), advanced oxidation protein products (AOPP), prooxidant-antioxidant balance (PAB) and C-reactive protein (CRP) were significantly higher in patients compared to CG (P < 0.001) and correlated negatively with TL in both patients and CG (P < 0.001). PCA showed a relation between PAB and TL, and between the EGFR status and TL. Oxidative stress and PBL telomere shortening are probably associated with LC development and progression.

• MeSH
• analýza hlavních komponent MeSH
• leukocyty metabolismus   MeSH
• lidé MeSH
• nádory plic * genetika   metabolismus   MeSH
• oxidační stres MeSH
• telomery MeSH
• zkracování telomer * MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH

Random Forest is an ensemble of decision trees based on the bagging and random subspace concepts. As suggested by Breiman, the strength of unstable learners and the diversity among them are the ensemble models' core strength. In this paper, we propose two approaches known as oblique and rotation double random forests. In the first approach, we propose rotation based double random forest. In rotation based double random forests, transformation or rotation of the feature space is generated at each node. At each node different random feature subspace is chosen for evaluation, hence the transformation at each node is different. Different transformations result in better diversity among the base learners and hence, better generalization performance. With the double random forest as base learner, the data at each node is transformed via two different transformations namely, principal component analysis and linear discriminant analysis. In the second approach, we propose oblique double random forest. Decision trees in random forest and double random forest are univariate, and this results in the generation of axis parallel split which fails to capture the geometric structure of the data. Also, the standard random forest may not grow sufficiently large decision trees resulting in suboptimal performance. To capture the geometric properties and to grow the decision trees of sufficient depth, we propose oblique double random forest. The oblique double random forest models are multivariate decision trees. At each non-leaf node, multisurface proximal support vector machine generates the optimal plane for better generalization performance. Also, different regularization techniques (Tikhonov regularization, axis-parallel split regularization, Null space regularization) are employed for tackling the small sample size problems in the decision trees of oblique double random forest. The proposed ensembles of decision trees produce trees with bigger size compared to the standard ensembles of decision trees as bagging is used at each non-leaf node which results in improved performance. The evaluation of the baseline models and the proposed oblique and rotation double random forest models is performed on benchmark 121 UCI datasets and real-world fisheries datasets. Both statistical analysis and the experimental results demonstrate the efficacy of the proposed oblique and rotation double random forest models compared to the baseline models on the benchmark datasets.

• MeSH
• algoritmy * MeSH
• analýza hlavních komponent MeSH
• rotace MeSH
• support vector machine * MeSH
• Publikační typ
• časopisecké články MeSH

AIM: Craniofacial growth demonstrates significant variation and is difficult to predict. The aim of the present investigation was twofold: (1) to assess the association (covariation) between craniofacial shape at pre- and post-adolescence and (2) to evaluate if pre-adolescent craniofacial shape is related (covaries) with growth magnitude and direction. SUBJECTS AND METHODS: One hundred fifty subjects (86 males and 64 females) untreated orthodontically were selected from AAOF Craniofacial Growth Legacy Collection. Each subject had cephalograms taken before 9 (pre-adolescent stage) and after 15 years of age (post-adolescent). Fourteen curves comprising 123 points (10 fixed and 113 sliding semilandmarks) comprehensively covering the craniofacial skeleton were digitally traced on each cephalogram. Procrustes alignment, principal component analysis, 2-block partial least squares (2B-PLS) analysis, and regression analysis were done after sliding the semilandmarks to minimize bending energy. RESULTS: The first 16 principal components (PCs) were non-trivial and explained 85.2% of total shape variability in the sample. PC1 depicted mainly variability in the vertical direction, PC2 represented mostly variability in the saddle angle and in the antero-posterior position of the mandible, and PC3 depicted primarily variability of the mandibular shape (steep versus flat mandibular plane). The covariation between pre- and post-adolescent facial shape was statistically significant, both in the pooled sample (RV coefficient = 0.604) and in boys (RV = 0.639) and girls (RV = 0.629). The pre-adolescent shape was weakly associated with the magnitude of facial change-2-block PLS analysis demonstrated that blocks 1 and 2 were independent (P = 0.118, RV = 0.035). CONCLUSIONS: The pre-adolescent shape of the craniofacial complex explained approximately 60% of the post-adolescent shape of the craniofacial complex; however, the relationship between pre-adolescent shape of the craniofacial complex and magnitude of its change was weak.

• MeSH
• analýza hlavních komponent MeSH
• kefalometrie MeSH
• lidé MeSH
• mandibula * MeSH
• maxila * MeSH
• mladiství MeSH
• obličej MeSH
• Check Tag
• lidé MeSH
• mladiství MeSH
• mužské pohlaví MeSH
• ženské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH

Induction of plant defences can show various levels of localization, which can optimize their efficiency. Locally induced responses may be particularly important in large plants, such as trees, that show high variability in traits and herbivory rates across their canopies. We studied the branch-localized induction of polyphenols, volatiles (VOCs), and changes in leaf protein content in Carpinus betulus L., Quercus robur L., and Tilia cordata L. in a common garden experiment. To induce the trees, we treated ten individuals per species on one branch with methyl jasmonate. Five other individuals per species served as controls. We measured the traits in the treated branches, in control branches on treated trees, and in control trees. Additionally, we ran predation assays and caterpillar food-choice trials to assess the effects of our treatment on other trophic levels. Induced VOCs included mainly mono- and sesquiterpenes. Their production was strongly localized to the treated branches in all three tree species studied. Treated trees showed more predation events than control trees. The polyphenol levels and total protein content showed a limited response to the treatment. Yet, winter moth caterpillars preferred leaves from control branches over leaves from treated branches within C. betulus individuals and leaves from control Q. robur individuals over leaves from treated Q. robur individuals. Our results suggest that there is a significant level of localization in induction of VOCs and probably also in unknown traits with direct effects on herbivores. Such localization allows trees to upregulate defences wherever and whenever they are needed.

• MeSH
• analýza hlavních komponent MeSH
• bukotvaré chemie   metabolismus   MeSH
• býložravci * MeSH
• hmyz MeSH
• obranné mechanismy proti býložravcům * MeSH
• stromy chemie   metabolismus   MeSH
• těkavé organické sloučeniny analýza   metabolismus   MeSH
• Tilia chemie   metabolismus   MeSH
• zvířata MeSH
• Check Tag
• zvířata MeSH
• Publikační typ
• časopisecké články MeSH
• srovnávací studie MeSH

BACKGROUND: Donor -specific HLA antibody (DSA) is present in many kidney transplant patients whose biopsies are classified as no rejection (NR). We explored whether in some NR kidneys DSA has subtle effects not currently being recognized. METHODS: We used microarrays to examine the relationship between standard-of-care DSA and rejection-related transcript increases in 1679 kidney transplant indication biopsies in the INTERCOMEX study (ClinicalTrials.gov NCT01299168), focusing on biopsies classified as NR by automatically assigned archetypal clustering. DSA testing results were available for 835 NR biopsies and were positive in 271 (32%). RESULTS: DSA positivity in NR biopsies was associated with mildly increased expression of antibody-mediated rejection (ABMR)-related transcripts, particularly IFNG-inducible and NK cell transcripts. We developed a machine learning DSA probability (DSAProb) classifier based on transcript expression in biopsies from DSA-positive versus DSA-negative patients, assigning scores using 10-fold cross-validation. This DSAProb classifier was very similar to a previously described "ABMR probability" classifier trained on histologic ABMR in transcript associations and prediction of molecular or histologic ABMR. Plotting the biopsies using Uniform Manifold Approximation and Projection revealed a gradient of increasing molecular ABMR-like transcript expression in NR biopsies, associated with increased DSA (P<2 × 10-16). In biopsies with no molecular or histologic rejection, increased DSAProb or ABMR probability scores were associated with increased risk of kidney failure over 3 years. CONCLUSIONS: Many biopsies currently considered to have no molecular or histologic rejection have mild increases in expression of ABMR-related transcripts, associated with increasing frequency of DSA. Thus, mild molecular ABMR-related pathology is more common than previously realized.

• MeSH
• analýza hlavních komponent MeSH
• analýza přežití MeSH
• biopsie MeSH
• čipová analýza tkání MeSH
• dárci tkání * MeSH
• exprese genu MeSH
• falešně negativní reakce MeSH
• genetická transkripce MeSH
• HLA antigeny imunologie   MeSH
• isoprotilátky imunologie   MeSH
• ledviny patologie   MeSH
• přežívání štěpu MeSH
• prospektivní studie MeSH
• rejekce štěpu genetika   MeSH
• specificita protilátek MeSH
• transplantace ledvin * MeSH
• transplantáty patologie   MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH