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Electroencephalography (EEG) represents a widely established method for assessing altered and typically developing brain function. However, systematic studies on EEG data quality, its correlates, and consequences are scarce. To address this research gap, the current study focused on the percentage of artifact-free segments after standard EEG pre-processing as a data quality index. We analyzed participant-related and methodological influences, and validity by replicating landmark EEG effects. Further, effects of data quality on spectral power analyses beyond participant-related characteristics were explored. EEG data from a multicenter ADHD-cohort (age range 6 to 45 years), and a non-ADHD school-age control group were analyzed (n\(_{total}\) = 305). Resting-state data during eyes open, and eyes closed conditions, and task-related data during a cued Continuous Performance Task (CPT) were collected. After pre-processing, general linear models, and stepwise regression models were fitted to the data. We found that EEG data quality was strongly related to demographic characteristics, but not to methodological factors. We were able to replicate maturational, task, and ADHD effects reported in the EEG literature, establishing a link with EEG-landmark effects. Furthermore, we showed that poor data quality significantly increases spectral power beyond effects of maturation and symptom severity. Taken together, the current results indicate that with a careful design and systematic quality control, informative large-scale multicenter trials characterizing neurophysiological mechanisms in neurodevelopmental disorders across the lifespan are feasible. Nevertheless, results are restricted to the limitations reported. Future work will clarify predictive value.
Objectives
Liver biopsies are the current gold standard in non-alcoholic steatohepatitis (NASH) diagnosis. Their invasive nature, however, still carries an increased risk for patients' health. The development of non-invasive diagnostic tools to differentiate between bland steatosis (NAFL) and NASH remains crucial. The aim of this study is the evaluation of investigated circulating microRNAs in combination with new targets in order to optimize the discrimination of NASH patients by non-invasive serum biomarkers.
Methods
Serum profiles of four microRNAs were evaluated in two cohorts consisting of 137 NAFLD patients and 61 healthy controls. In a binary logistic regression model microRNAs of relevance were detected. Correlation of microRNA appearance with known biomarkers like ALT and CK18-Asp396 was evaluated. A simplified scoring model was developed, combining the levels of microRNA in circulation and CK18-Asp396 fragments. Receiver operating characteristics were used to evaluate the potential of discriminating NASH.
Results
The new finding of our study is the different profile of circulating miR-21 in NASH patients (p<0.0001). Also, it validates recently published results of miR-122 and miR-192 to be differentially regulated in NAFL and NASH. Combined microRNA expression profiles with CK18-Asp396 fragment level scoring model had a higher potential of NASH prediction compared to other risk biomarkers (AUROC = 0.83, 95% CI = 0.754-0.908; p<0.001). Evaluation of score model for NAFL (Score = 0) and NASH (Score = 4) had shown high rates of sensitivity (91%) and specificity (83%).
Conclusions
Our study defines candidates for a combined model of miRNAs and CK18-Asp396 levels relevant as a promising expansion for diagnosis and in turn treatment of NASH.
The aim of the present work is the development and implementation of new simulation
possibilities for the CAST program package. Development included, among other
things, the partial parallelization of the already existing force fields, extension of the
treatment of electrostatic interactions and implementation of molecular dynamics and
free energy algorithms.
The most time consuming part of force field calculations is the evaluation of the nonbonded
interactions. The calculation of these interactions has been parallelized and
it could be shown to yield a significant speed up for multi-core calculations compared
to the serial execution on only one CPU. For both, simple energy/gradient as well as
molecular dynamics simulations the computational time could be significantly reduced.
To further increase the performance of calculations employing a cutoff radius, a linkedcell
algorithm was implemented which is able to build up the non-bonded interaction
list up to 7 times faster than the original algorithm.
To provide access to dynamic properties based on the natural time evolution of a system,
a molecular dynamics code has been implemented. The MD implementation features
two integration schemes for the equations of motion which are able to generate stable
trajectories. The basic MD algorithm as described in Section 1.2 leads to the sampling
in the microcanonical (NVE) ensemble. The practical use of NVE simulations is limited
though because it does not correspond to any experimentally realistic situation.
More realistic simulation conditions are found in the isothermal (NVT) and isothermalisobaric
(NPT) ensembles. To generate those ensembles, temperature and pressure
control has been implemented. The temperature can be controlled in two ways: by direct
velocity scaling and by a Nose-Hoover thermostat which produces a real canonical
ensemble. The pressure coupling is realized by implementation of a Berendsen barostat.
The pressure coupling can be used for isotropic or anisotropic box dimensions with the
restriction that the angles of the box need to be 90. A crucial simulation parameter in
MD simulations is the length of the timestep. The timestep is usually in the rang of 1fs.
Increasing the timestep beyond 1fs can lead to unstable trajectories since the fastest
motion in the system, usually the H-X stretch vibration can not be sampled anymore.
A way to allow for bigger timesteps is the use of a constraint algorithm which constrains the H-X bonds to the equilibrium distance. For this the RATTLE algorithm has been
implemented in the CAST program. The velocity Verlet algorithm in combination with
the RATTLE algorithm has been shown to yield stable trajectories for an arbitrary
length of simulation time. In a first application the MD implementation is used in conjunction
with the MOPAC interface for the investigation of PBI sidechains and their
rigidity. The theoretical investigations show a nice agreement with experimentally obtained
results. Based on the MD techniques two algorithms for the determination of free
energy differences have been implemented. The umbrella sampling algorithm can be
used to determine the free energy change along a reaction coordinate based on distances
or dihedral angles. The implementation was tested on the stretching of a deca-L-alanine
and the rotation barrier of butane in vacuum. The results are in nearly perfect agreement
with literature values. For the FEP implementation calculations were performed
for a zero-sum transformation of ethane in explicit solvent, the charging of a sodium
ion in explicit solvent and the transformations of a tripeptide in explicit solvent. All
results are in agreement with benchmark calculations of the NAMD program as well
as literature values. The FEP formalism was then applied to determine the relative
binding free energies between two inhibitors in an inhibitor-protein complex.
Next to force fields, ab-initio methods can be used for simulations and global optimizations.
Since the performance of such methods is usually significantly poorer than force
field applications, the use for global optimizations is limited. Nevertheless significant
progress has been made by porting these codes to GPUs. In order to make use of these
developments a MPI interface has been implemented into CAST for communication
with the DFT code TeraChem. The CAST/TeraChem combination has been tested
on the $H_2 O_{10}$ cluster as well as the polypeptide met-Enkephalin. The pure ab-initio
calculations showed a superior behavior compared to the standard procedure where the
force field results are usually refined using quantum chemical methods.
Breast cancer is the most common cancer among women worldwide. Every year, nearly 1.4 million new cases of breast cancer are diagnosed, and about 450.000 women die of the disease. Approximately 15-25% of breast cancer cases exhibit increased quantities of the trans-membrane receptor tyrosine kinase human epidermal growth factor receptor 2 (HER2) on the tumor cell surface. Previous studies showed that blockade of this HER2 proto-oncogene with the antibody trastuzumab substantially improved the overall survival of patients with this aggressive type of breast cancer. Recruitment of natural killer (NK) cells and subsequent induction of antibody-dependent cell-mediated cytotoxicity (ADCC) contributed to this beneficial effect. We hypothesized that antibody binding to HER2-positive breast cancer cells and thus ADCC might be further improved by synergistically applying two different HER2-specific antibodies, trastuzumab and pertuzumab. We found that tumor cell killing via ADCC was increased when the combination of trastuzumab, pertuzumab, and NK cells was applied to HER2-positive breast cancer cells, as compared to the extent of ADCC induced by a single antibody. Furthermore, a subset of \(CD44^{high}CD24^{low}HER2^{low}\) cells, which possessed characteristics of cancer stem cells, could be targeted more efficiently by the combination of two HER2-specific antibodies compared to the efficiency of one antibody. These in vitro results demonstrated the immunotherapeutic benefit achieved by the combined application of trastuzumab and pertuzumab. These findings are consistent with the positive results of the clinical studies, CLEOPATRA and NEOSPHERE, conducted with patients that had HER2-positive breast cancer. Compared to a single antibody treatment, the combined application of trastuzumab and pertuzumab showed a stronger ADCC effect and improved the targeting of breast cancer stem cells.
We aimed to compare the clinical data at first presentation to inpatient treatment of children (<14 years) vs. adolescents (≥14 years) with anorexia nervosa (AN), focusing on duration of illness before hospital admission and body mass index (BMI) at admission and discharge, proven predictors of the outcomes of adolescent AN. Clinical data at first admission and at discharge in 289 inpatients with AN (children: n = 72; adolescents: n = 217) from a German multicenter, web-based registry for consecutively enrolled patients with childhood and adolescent AN were analyzed. Inclusion criteria were a maximum age of 18 years, first inpatient treatment due to AN, and a BMI <10th BMI percentile at admission. Compared to adolescents, children with AN had a shorter duration of illness before admission (median: 6.0 months vs. 8.0 months, p = 0.004) and higher BMI percentiles at admission (median: 0.7 vs. 0.2, p = 0.004) as well as at discharge (median: 19.3 vs. 15.1, p = 0.011). Thus, in our study, children with AN exhibited clinical characteristics that have been associated with better outcomes, including higher admission and discharge BMI percentile. Future studies should examine whether these factors are actually associated with positive long-term outcomes in children.