Learning Impact of a Virtual Brain Electrical Activity Simulator Among Neurophysiology Students: Mixed-Methods Intervention Study

Background:Virtual simulation is the re-creation of reality depicted on a computer screen. It offers the possibility to exercise motor and psychomotor skills. In biomedical and medical education, there is an attempt to find new ways to support students’ learning in neurophysiology. Traditionally, recording electroencephalography (EEG) has been learned through practical hands-on exercises. To date, virtual simulations of EEG measurements have not been used.Objective:This study aimed to examine the development of students’ theoretical knowledge and practical skills in the EEG measurement when using a virtual EEG simulator in biomedical laboratory science in the context of a neurophysiology course.Methods:A computer-based EEG simulator was created. The simulator allowed virtual electrode placement and EEG graph interpretation. The usefulness of the simulator for learning EEG measurement was tested with 35 participants randomly divided into three equal groups. Group 1 (experimental group 1) used the simulator with fuzzy feedback, group 2 (experimental group 2) used the simulator with exact feedback, and group 3 (control group) did not use a simulator. The study comprised pre- and posttests on theoretical knowledge and practical hands-on evaluation of EEG electrode placement.Results:The Wilcoxon signed-rank test indicated that the two groups that utilized a computer-based electrode placement simulator showed significant improvement in both theoretical knowledge (Z=1.79, P=.074) and observed practical skills compared with the group that studied without a simulator.Conclusions:Learning electrode placement using a simulator enhances students’ ability to place electrodes and, in combination with practical hands-on training, increases their understanding of EEG measurement.</p

Characteristics and sources of fluorescent aerosols in the central Arctic Ocean

The Arctic is sensitive to cloud radiative forcing. Due to the limited number of aerosols present throughout much of the year, cloud formation is susceptible to the presence of cloud condensation nuclei and ice nucleating particles (INPs). Primary biological aerosol particles (PBAP) contribute to INPs and can impact cloud phase, lifetime, and radiative properties. We present yearlong observations of hyperfluorescent aerosols (HFA), tracers for PBAP, conducted with a Wideband Integrated Bioaerosol Sensor, New Electronics Option during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition (October 2019–September 2020) in the central Arctic. We investigate the influence of potential anthropogenic and natural sources on the characteristics of the HFA and relate our measurements to INP observations during MOSAiC. Anthropogenic sources influenced HFA during the Arctic haze period. But surprisingly, we also found sporadic “bursts” of HFA with the characteristics of PBAP during this time, albeit with unclear origin. The characteristics of HFA between May and August 2020 and in October 2019 indicate a strong contribution of PBAP to HFA. Notably from May to August, PBAP coincided with the presence of INPs nucleating at elevated temperatures, that is, &amp;gt;−9°C, suggesting that HFA contributed to the “warm INP” concentration. The air mass residence time and area between May and August and in October were dominated by the open ocean and sea ice, pointing toward PBAP sources from within the Arctic Ocean. As the central Arctic changes drastically due to climate warming with expected implications on aerosol–cloud interactions, we recommend targeted observations of PBAP that reveal their nature (e.g., bacteria, diatoms, fungal spores) in the atmosphere and in relevant surface sources, such as the sea ice, snow on sea ice, melt ponds, leads, and open water, to gain further insights into the relevant source processes and how they might change in the future.</jats:p

A systematic, large-scale comparison of transcription factor binding site models

Background The modelling of gene regulation is a major challenge in biomedical research. This process is dominated by transcription factors (TFs) and mutations in their binding sites (TFBSs) may cause the misregulation of genes, eventually leading to disease. The consequences of DNA variants on TF binding are modelled in silico using binding matrices, but it remains unclear whether these are capable of accurately representing in vivo binding. In this study, we present a systematic comparison of binding models for 82 human TFs from three freely available sources: JASPAR matrices, HT-SELEX-generated models and matrices derived from protein binding microarrays (PBMs). We determined their ability to detect experimentally verified “real” in vivo TFBSs derived from ENCODE ChIP-seq data. As negative controls we chose random downstream exonic sequences, which are unlikely to harbour TFBS. All models were assessed by receiver operating characteristics (ROC) analysis. Results While the area- under-curve was low for most of the tested models with only 47 % reaching a score of 0.7 or higher, we noticed strong differences between the various position-specific scoring matrices with JASPAR and HT-SELEX models showing higher success rates than PBM-derived models. In addition, we found that while TFBS sequences showed a higher degree of conservation than randomly chosen sequences, there was a high variability between individual TFBSs. Conclusions Our results show that only few of the matrix-based models used to predict potential TFBS are able to reliably detect experimentally confirmed TFBS. We compiled our findings in a freely accessible web application called ePOSSUM (http:/mutationtaster.charite.de/ePOSSUM/) which uses a Bayes classifier to assess the impact of genetic alterations on TF binding in user-defined sequences. Additionally, ePOSSUM provides information on the reliability of the prediction using our test set of experimentally confirmed binding sites

Body indices and basic vital signs in Helicobacter pylori positive and negative persons

It has been hypothesized that Helicobacter pylori (Hp) infection may contribute to reduced stature, risk of hypertension or obesity. The aim was to evaluate body indices in Hp positive and negative persons. A total of 2436 subjects (4–100 years old) were tested for Hp status by 13Curea breath test. Data on height and weight were collected for 84%, and blood pressure for 80% of the study subjects. The prevalence of Hp infection was 41.6%. The odds ratio for a 10-year increase in age was 1.21 (95% CI 1.17–1.25, p-value <0.001). Statistically significant negative association of Hp positivity with body height was most pronounced in the younger age groups, while a positive association of Hp positivity with body mass index was only seen in those aged 15+ years. There was a negative effect of Hp positivity on systolic and diastolic blood pressure in subjects below 25 and a relatively strong positive effect on blood pressure in subjects over 65 years. Residual confounding by social characteristics as a possible explanation for the associations of Hp positivity with height and blood pressure cannot be excluded. Unmeasured factors related to social and family environment may cause the apparent association between Hp positivity and children’s growth and blood pressure

Consequences of the size structure of fish populations for their effects on a generalist avian predator

Size-structured interspecific interactions can shift between predation and competition, depending on ontogenetic changes in size relationships. I examined the effects of common carp (Cyprinus carpio), an omnivorous fish, on the reproductive success of the red-necked grebe (Podiceps grisegena), an avian gape-limited predator, along a fish size gradient created by stocking distinct age-cohorts in seminatural ponds. Young-of-the-year (0+) carp were an essential food source for young grebes. Only adult birds were able to consume 1-year-old (1+) fish, while 2-year-old (2+) fish attained a size refuge from grebes. Amphibian larvae were the principal alternative prey to fish, followed by macroinvertebrates, but the abundance of both dramatically decreased along the carp size gradient. Fledging success was 2.8 times greater in ponds with 0+ versus 1+ carp; in ponds with 1+ carp, chicks received on average 2.6–3 times less prey biomass from their parents, and over 1/3 of broods suffered total failure. Breeding birds avoided settling on 2+ ponds. These results show that changes in prey fish size structure can account for shifts from positive trophic effects on the avian predator to a negative impact on the predator’s alternative resources. However, competition did not fully explain the decrease in grebe food resources in the presence of large fish, as carp and grebes overlapped little in diet. In experimental cages, 1+ carp totally eliminated young larvae of amphibians palatable to fish. In field conditions, breeding adults of palatable taxa avoided ponds with 1+ and older carp. Non-trophic interactions such as habitat selection by amphibians or macroinvertebrates to avoid large fish may provide an indirect mechanism strengthening the adverse bottom-up effects of fish on birds

Text Mining Improves Prediction of Protein Functional Sites

We present an approach that integrates protein structure analysis and text mining for protein functional site prediction, called LEAP-FS (Literature Enhanced Automated Prediction of Functional Sites). The structure analysis was carried out using Dynamics Perturbation Analysis (DPA), which predicts functional sites at control points where interactions greatly perturb protein vibrations. The text mining extracts mentions of residues in the literature, and predicts that residues mentioned are functionally important. We assessed the significance of each of these methods by analyzing their performance in finding known functional sites (specifically, small-molecule binding sites and catalytic sites) in about 100,000 publicly available protein structures. The DPA predictions recapitulated many of the functional site annotations and preferentially recovered binding sites annotated as biologically relevant vs. those annotated as potentially spurious. The text-based predictions were also substantially supported by the functional site annotations: compared to other residues, residues mentioned in text were roughly six times more likely to be found in a functional site. The overlap of predictions with annotations improved when the text-based and structure-based methods agreed. Our analysis also yielded new high-quality predictions of many functional site residues that were not catalogued in the curated data sources we inspected. We conclude that both DPA and text mining independently provide valuable high-throughput protein functional site predictions, and that integrating the two methods using LEAP-FS further improves the quality of these predictions

Previous Lung Diseases and Lung Cancer Risk: A Systematic Review and Meta-Analysis

In order to review the epidemiologic evidence concerning previous lung diseases as risk factors for lung cancer, a meta-analysis and systematic review was conducted.Relevant studies were identified through MEDLINE searches. Using random effects models, summary effects of specific previous conditions were evaluated separately and combined. Stratified analyses were conducted based on smoking status, gender, control sources and continent.A previous history of COPD, chronic bronchitis or emphysema conferred relative risks (RR) of 2.22 (95% confidence interval (CI): 1.66, 2.97) (from 16 studies), 1.52 (95% CI: 1.25, 1.84) (from 23 studies) and 2.04 (95% CI: 1.72, 2.41) (from 20 studies), respectively, and for all these diseases combined 1.80 (95% CI: 1.60, 2.11) (from 39 studies). The RR of lung cancer for subjects with a previous history of pneumonia was 1.43 (95% CI: 1.22-1.68) (from 22 studies) and for subjects with a previous history of tuberculosis was 1.76 (95% CI=1.49, 2.08), (from 30 studies). Effects were attenuated when restricting analysis to never smokers only for COPD/emphysema/chronic bronchitis (RR=1.22, 0.97-1.53), however remained significant for pneumonia 1.36 (95% CI: 1.10, 1.69) (from 8 studies) and tuberculosis 1.90 (95% CI: 1.45, 2.50) (from 11 studies).Previous lung diseases are associated with an increased risk of lung cancer with the evidence among never smokers supporting a direct relationship between previous lung diseases and lung cancer