BACKGROUND: The cerebellum is one of the major central nervous structures consistently altered in obesity. Its role in higher cognitive function, parts of which are affected by obesity, is mediated through projections to and from the cerebral cortex. We therefore investigated the relationship between body mass index (BMI) and cerebellocerebral connectivity. METHODS: We utilized the Human Connectome Project's Young Adults dataset, including functional magnetic resonance imaging (fMRI) and behavioral data, to perform connectome-based predictive modeling (CPM) restricted to cerebellocerebral connectivity of resting-state fMRI and task-based fMRI. We developed a Python-based open-source framework to perform CPM, a data-driven technique with built-in cross-validation to establish brain-behavior relationships. Significance was assessed with permutation analysis. RESULTS: We found that (i) cerebellocerebral connectivity predicted BMI, (ii) task-general cerebellocerebral connectivity predicted BMI more reliably than resting-state fMRI and individual task-based fMRI separately, (iii) predictive networks derived this way overlapped with established functional brain networks (namely, frontoparietal networks, the somatomotor network, the salience network, and the default mode network), and (iv) we found there was an inverse overlap between networks predictive of BMI and networks predictive of cognitive measures adversely affected by overweight/obesity. CONCLUSIONS: Our results suggest obesity-specific alterations in cerebellocerebral connectivity, specifically with regard to task execution. With brain areas and brain networks relevant to task performance implicated, these alterations seem to reflect a neurobiological substrate for task performance adversely affected by obesity.

• Klíčová slova
• BMI, Human Connectome Project (HCP), Python, cerebellum, connectome-based predictive modeling, functional magnetic resonance imaging (fMRI),
• MeSH
• dospělí MeSH
• index tělesné hmotnosti * MeSH
• konektom * metody   MeSH
• lidé MeSH
• magnetická rezonanční tomografie * metody   MeSH
• mladý dospělý MeSH
• mozeček * diagnostické zobrazování   fyziologie   MeSH
• nervová síť diagnostické zobrazování   fyziologie   MeSH
• obezita diagnostické zobrazování   MeSH
• Check Tag
• dospělí MeSH
• lidé MeSH
• mladý dospělý MeSH
• mužské pohlaví MeSH
• ženské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH

PRIMARY OBJECTIVE: To assess predisposing and precipitating risk factors and create a predictive model for post-stroke delirium. RESEARCH DESIGN: A prospective observational study in a cohort of consecutive patients with ischemic stroke or intracerebral haematoma admitted within 24 hours of stroke onset. METHODS: Patients were assessed daily for delirium during the first week by means of DSM-IV criteria and risk factors were recorded. RESULTS: One hundred patients completed a 7-day evaluation (47 women and 53 men, median age 77 years). An episode of delirium was detected in 43 patients (43%). Using multivariate logistic regression, a predictive statistical model was developed that utilized independent risk factors: age (OR = 1.08; 95% CI = 1.02-1.15); intracerebral haemorrhage (OR = 6.11; 95% CI = 1.62-22.98), lesion volume > 40 ccm (OR = 3.99; 95% CI = 1.29-12.39) and either elevated gamma-glytamyl transferase (OR = 4.88; 95% CI = 1.45-16.35) and elevated serum bilirubin (OR = 3.70; 95% CI = 1.32-10.38) or maximum sequential organ failure assessment score >2 (OR = 3.33; 95% CI = 1.06-10.45) with acceptable sensitivity and specificity (69.0% and 80.7%). In ischemic strokes, total anterior circulation infarctions were more frequently associated with delirium (73.3% developed delirium) compared with the remainder of the groups combined (p = 0.004; OR = 6.66; 95% CI = 1.85-24.01). CONCLUSION: Higher age, metabolic disturbances, intracerebral haemorrhage and larger ischemic hemispheric strokes increase the risk of post-stroke delirium.

• MeSH
• bilirubin krev   MeSH
• C-reaktivní protein metabolismus   MeSH
• časové faktory MeSH
• cerebrální krvácení krev   komplikace   patofyziologie   MeSH
• cévní mozková příhoda krev   komplikace   patofyziologie   MeSH
• delirium krev   etiologie   patofyziologie   MeSH
• Diagnostický a statistický manuál mentálních poruch MeSH
• gama-glutamyltransferasa krev   MeSH
• lidé MeSH
• míra přežití MeSH
• prediktivní hodnota testů MeSH
• prognóza MeSH
• prospektivní studie MeSH
• rizikové faktory MeSH
• senioři MeSH
• teoretické modely MeSH
• věkové faktory MeSH
• Check Tag
• lidé MeSH
• mužské pohlaví MeSH
• senioři MeSH
• ženské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH
• Názvy látek
• bilirubin MeSH
• C-reaktivní protein MeSH
• gama-glutamyltransferasa MeSH

Clinical indicators of heart function are often limited in their ability to accurately evaluate the current mechanical state of the myocardium. Biomechanical modeling has been shown to be a promising tool in addition to clinical indicators. By providing a patient-specific measure of myocardial active stress (contractility), biomechanical modeling can enhance the precision of the description of patient's pathophysiology at any given point in time. In this work we aim to explore the ability of biomechanical modeling to predict the response of ventricular mechanics to the progressively decreasing afterload in repaired tetralogy of Fallot (rTOF) patients undergoing pulmonary valve replacement (PVR) for significant residual right ventricular outflow tract obstruction (RVOTO). We used 19 patient-specific models of patients with rTOF prior to pulmonary valve replacement (PVR), denoted as PSMpre, and patient-specific models of the same patients created post-PVR (PSMpost)-both created in our previous published work. Using the PSMpre and assuming cessation of the pulmonary regurgitation and a progressive decrease of RVOT resistance, we built relationships between the contractility and RVOT resistance post-PVR. The predictive value of such in silico obtained relationships were tested against the PSMpost, i.e. the models created from the actual post-PVR datasets. Our results show a linear 1-dimensional relationship between the in silico predicted contractility post-PVR and the RVOT resistance. The predicted contractility was close to the contractility in the PSMpost model with a mean (± SD) difference of 6.5 (± 3.0)%. The relationships between the contractility predicted by in silico PVR vs. RVOT resistance have a potential to inform clinicians about hypothetical mechanical response of the ventricle based on the degree of pre-operative RVOTO.

• Klíčová slova
• Biomechanical modeling, Myocardial contractility, Valve replacement, Valvular heart disease, Ventricular overload,
• MeSH
• biomechanika MeSH
• chirurgická náhrada chlopně MeSH
• Fallotova tetralogie chirurgie   MeSH
• individualizovaná medicína * MeSH
• lidé MeSH
• modely kardiovaskulární MeSH
• obstrukce výtoku ze srdeční komory patofyziologie   chirurgie   MeSH
• plicní chlopeň chirurgie   MeSH
• pooperační komplikace patofyziologie   chirurgie   MeSH
• prediktivní hodnota testů MeSH
• remodelace komor MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH

Presented paper deals with a novel application of the (nonlinear) logistic equation to model an elimination of microscopic filaments types of fungi-molds from affected materials via different external inactivation techniques. It is shown that if the inactivation rate of the external source is greater than the maximum natural growth rate of mycelium, the mold colony becomes destroyed after a finite time. Otherwise, the mycelium may survive the external attack only at a sufficiently large initial concentration of the inoculum. Theoretically determined growth curves are compared with the experimental data for Aspergillus brasiliensis mold inactivated by using both cold atmospheric plasma (CAP) and UV-germicidal lamp. Model presented in the article may be applied also to other classes of microorganisms (e.g. bacteria).

• MeSH
• Aspergillus * růst a vývoj   fyziologie   MeSH
• biologické modely MeSH
• houby MeSH
• mycelium růst a vývoj   MeSH
• plazmové plyny farmakologie   MeSH
• ultrafialové záření MeSH
• Publikační typ
• časopisecké články MeSH

Spondylotic cervical cord compression detected by imaging methods is a prerequisite for the clinical diagnosis of spondylotic cervical myelopathy (SCM). Little is known about the spontaneous course and prognosis of clinically "silent" presymptomatic spondylotic cervical cord compression (P-SCCC). The aim of the present study was to update a previously published model predictive for the development of clinically symptomatic SCM, and to assess the early and late risks of this event in a larger cohort of P-SCCC subjects. A group of 199 patients (94 women, 105 men, median age 51 years) with magnetic resonance signs of spondylotic cervical cord compression, but without clear clinical signs of myelopathy, was followed prospectively for at least 2 years (range 2-12 years). Various demographic, clinical, imaging, and electrophysiological parameters were correlated with the time for the development of symptomatic SCM. Clinical evidence of the first signs and symptoms of SCM within the follow-up period was found in 45 patients (22.6%). The 25th percentile time to clinically manifested myelopathy was 48.4 months, and symptomatic SCM developed within 12 months in 16 patients (35.5%). The presence of symptomatic cervical radiculopathy and electrophysiological abnormalities of cervical cord dysfunction detected by somatosensory or motor-evoked potentials were associated with time-to-SCM development and early development (< or =12 months) of SCM, while MRI hyperintensity predicted later (>12 months) progression to symptomatic SCM. The multivariate predictive model based on these variables correctly predicted early progression into SCM in 81.4% of the cases. In conclusion, electrophysiological abnormalities of cervical cord dysfunction together with clinical signs of cervical radiculopathy and MRI hyperintensity are useful predictors of early progression into symptomatic SCM in patients with P-SCCC. Electrophysiological evaluation of cervical cord dysfunction in patients with cervical radiculopathy or back pain is valuable. Meticulous follow-up is justified in high-risk P-SCCC cases.

• MeSH
• dospělí MeSH
• elektrodiagnostika metody   MeSH
• evokované potenciály fyziologie   MeSH
• kohortové studie MeSH
• komprese míchy diagnóza   patofyziologie   MeSH
• krční obratle patologie   patofyziologie   MeSH
• lidé středního věku MeSH
• lidé MeSH
• magnetická rezonanční tomografie MeSH
• mícha patofyziologie   MeSH
• modely neurologické * MeSH
• nervové dráhy patofyziologie   MeSH
• osteofytóza páteře diagnóza   patofyziologie   MeSH
• prediktivní hodnota testů MeSH
• prognóza MeSH
• progrese nemoci MeSH
• prospektivní studie MeSH
• radikulopatie diagnóza   patofyziologie   MeSH
• senioři nad 80 let MeSH
• senioři MeSH
• Check Tag
• dospělí MeSH
• lidé středního věku MeSH
• lidé MeSH
• mužské pohlaví MeSH
• senioři nad 80 let MeSH
• senioři MeSH
• ženské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH

INTRODUCTION: Aim of this study is to validate some constitutive models by assessing their capabilities in describing and predicting uniaxial and biaxial behavior of porcine aortic tissue. METHODS: 14 samples from porcine aortas were used to perform 2 uniaxial and 5 biaxial tensile tests. Transversal strains were furthermore stored for uniaxial data. The experimental data were fitted by four constitutive models: Holzapfel-Gasser-Ogden model (HGO), model based on generalized structure tensor (GST), Four-Fiber-Family model (FFF) and Microfiber model. Fitting was performed to uniaxial and biaxial data sets separately and descriptive capabilities of the models were compared. Their predictive capabilities were assessed in two ways. Firstly each model was fitted to biaxial data and its accuracy (in term of R2 and NRMSE) in prediction of both uniaxial responses was evaluated. Then this procedure was performed conversely: each model was fitted to both uniaxial tests and its accuracy in prediction of 5 biaxial responses was observed. RESULTS: Descriptive capabilities of all models were excellent. In predicting uniaxial response from biaxial data, microfiber model was the most accurate while the other models showed also reasonable accuracy. Microfiber and FFF models were capable to reasonably predict biaxial responses from uniaxial data while HGO and GST models failed completely in this task. CONCLUSIONS: HGO and GST models are not capable to predict biaxial arterial wall behavior while FFF model is the most robust of the investigated constitutive models. Knowledge of transversal strains in uniaxial tests improves robustness of constitutive models.

• Klíčová slova
• Constitutive modeling, Arterial biomechanics, Mechanical testing, Uniaxial – biaxial tension,
• MeSH
• aorta thoracica * MeSH
• biologické modely * MeSH
• biomechanika MeSH
• mechanické jevy * MeSH
• pevnost v tahu MeSH
• prasata MeSH
• testování materiálů MeSH
• zvířata MeSH
• Check Tag
• zvířata MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH

BACKGROUND: The presence of ACPA significantly increases the risk of developing RA. Dysregulation of lymphocyte subpopulations was previously described in RA. Our objective was to propose the predictive model for progression to clinical arthritis based on peripheral lymphocyte subsets and ACPA in individuals who are at risk of RA. METHODS: Our study included 207 at-risk individuals defined by the presence of arthralgias and either additional ACPA positivity or meeting the EULAR definition for clinically suspect arthralgia. For the construction of predictive models, 153 individuals with symptom duration ≥12 months who have not yet progressed to arthritis were included. The lymphocyte subsets were evaluated using flow cytometry and anti-CCP using ELISA. RESULTS: Out of all individuals with arthralgia, 41 progressed to arthritis. A logistic regression model with baseline peripheral blood lymphocyte subpopulations and ACPA as predictors was constructed. The resulting predictive model showed that high anti-CCP IgG, higher percentage of CD4+ T cells, and lower percentage of T and NK cells increased the probability of arthritis development. Moreover, the proposed classification decision tree showed that individuals having both high anti-CCP IgG and low NK cells have the highest risk of developing arthritis. CONCLUSIONS: We propose a predictive model based on baseline levels of lymphocyte subpopulations and ACPA to identify individuals with arthralgia with the highest risk of progression to clinical arthritis. The final model includes T cells and NK cells, which are involved in the pathogenesis of RA. This preliminary model requires further validation in larger at-risk cohorts.

• Klíčová slova
• ACPA, NK cells, arthralgia, pre-RA,
• MeSH
• artralgie * imunologie   MeSH
• dospělí MeSH
• lidé středního věku MeSH
• lidé MeSH
• podskupiny lymfocytů * imunologie   MeSH
• prediktivní hodnota testů MeSH
• progrese nemoci * MeSH
• protilátky proti citrulinovaným peptidům * krev   imunologie   MeSH
• revmatoidní artritida * imunologie   krev   MeSH
• Check Tag
• dospělí MeSH
• lidé středního věku MeSH
• lidé MeSH
• mužské pohlaví MeSH
• ženské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH
• Názvy látek
• protilátky proti citrulinovaným peptidům * MeSH

Primary rat hepatocytes were used to test acute toxicities of 16 neutral aliphatic alcohols, ketones and esters. Their effects on cell viability and metabolic function (ureogenesis, i.e. biotransformation of ornithine to urea) were measured and expressed as EC50 values. Log EC50 values from both tests correlated with the log partition coefficients for the chemicals between n-octanol and water and log P(ow)-based QSAR models were derived. Log EC50 (viability) tightly correlates with log EC50 (ureogenesis): log EC50 (viability)=0.91 log EC50 (ureogenesis)+0.06. Each of these toxic indices can be substituted by the other one. The toxic indices for both cell viability and metabolic disorder can be estimated using log EC50 for movement inhibition in the oligochaete Tubifex tubifex and the respective QSAR equation. It eliminates a usage of rats. Their correlations were proved and justified.

• MeSH
• barvicí látky MeSH
• fyzikální chemie MeSH
• hepatocyty účinky léků   metabolismus   MeSH
• indikátory a reagencie MeSH
• krysa rodu Rattus MeSH
• kultivované buňky MeSH
• kvantitativní vztahy mezi strukturou a aktivitou * MeSH
• močovina metabolismus   MeSH
• potkani Wistar MeSH
• prediktivní hodnota testů MeSH
• roztoky MeSH
• separace buněk MeSH
• toxikologie metody   MeSH
• trypanová modř MeSH
• vztah mezi dávkou a účinkem léčiva MeSH
• zvířata MeSH
• Check Tag
• krysa rodu Rattus MeSH
• mužské pohlaví MeSH
• zvířata MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH
• Názvy látek
• barvicí látky MeSH
• indikátory a reagencie MeSH
• močovina MeSH
• roztoky MeSH
• trypanová modř MeSH

During the minimally-invasive liver surgery, only the partial surface view of the liver is usually provided to the surgeon via the laparoscopic camera. Therefore, it is necessary to estimate the actual position of the internal structures such as tumors and vessels from the pre-operative images. Nevertheless, such task can be highly challenging since during the intervention, the abdominal organs undergo important deformations due to the pneumoperitoneum, respiratory and cardiac motion and the interaction with the surgical tools. Therefore, a reliable automatic system for intra-operative guidance requires fast and reliable registration of the pre- and intra-operative data. In this paper we present a complete pipeline for the registration of pre-operative patient-specific image data to the sparse and incomplete intra-operative data. While the intra-operative data is represented by a point cloud extracted from the stereo-endoscopic images, the pre-operative data is used to reconstruct a biomechanical model which is necessary for accurate estimation of the position of the internal structures, considering the actual deformations. This model takes into account the patient-specific liver anatomy composed of parenchyma, vascularization and capsule, and is enriched with anatomical boundary conditions transferred from an atlas. The registration process employs the iterative closest point technique together with a penalty-based method. We perform a quantitative assessment based on the evaluation of the target registration error on synthetic data as well as a qualitative assessment on real patient data. We demonstrate that the proposed registration method provides good results in terms of both accuracy and robustness w.r.t. the quality of the intra-operative data.

• Klíčová slova
• Minimally-invasive surgery, Non-rigid registration, Patient-specific modeling, Real-time simulation,
• MeSH
• biologické modely * MeSH
• individualizovaná medicína metody   MeSH
• játra chirurgie   MeSH
• lidé MeSH
• miniinvazivní chirurgické výkony metody   MeSH
• Check Tag
• lidé MeSH
• mužské pohlaví MeSH
• ženské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH

Affinity fingerprints report the activity of small molecules across a set of assays, and thus permit to gather information about the bioactivities of structurally dissimilar compounds, where models based on chemical structure alone are often limited, and model complex biological endpoints, such as human toxicity and in vitro cancer cell line sensitivity. Here, we propose to model in vitro compound activity using computationally predicted bioactivity profiles as compound descriptors. To this aim, we apply and validate a framework for the calculation of QSAR-derived affinity fingerprints (QAFFP) using a set of 1360 QSAR models generated using Ki, Kd, IC50 and EC50 data from ChEMBL database. QAFFP thus represent a method to encode and relate compounds on the basis of their similarity in bioactivity space. To benchmark the predictive power of QAFFP we assembled IC50 data from ChEMBL database for 18 diverse cancer cell lines widely used in preclinical drug discovery, and 25 diverse protein target data sets. This study complements part 1 where the performance of QAFFP in similarity searching, scaffold hopping, and bioactivity classification is evaluated. Despite being inherently noisy, we show that using QAFFP as descriptors leads to errors in prediction on the test set in the ~ 0.65-0.95 pIC50 units range, which are comparable to the estimated uncertainty of bioactivity data in ChEMBL (0.76-1.00 pIC50 units). We find that the predictive power of QAFFP is slightly worse than that of Morgan2 fingerprints and 1D and 2D physicochemical descriptors, with an effect size in the 0.02-0.08 pIC50 units range. Including QSAR models with low predictive power in the generation of QAFFP does not lead to improved predictive power. Given that the QSAR models we used to compute the QAFFP were selected on the basis of data availability alone, we anticipate better modeling results for QAFFP generated using more diverse and biologically meaningful targets. Data sets and Python code are publicly available at https://github.com/isidroc/QAFFP_regression .

• Klíčová slova
• Affinity fingerprints, Bioactivity modeling, ChEMBL, Cytotoxicity, Drug sensitivity, Drug sensitivity prediction, QSAR,
• Publikační typ
• časopisecké články MeSH