Complexity of bacterial communities in a river-floodplain system (Danube, Austria)

Natural floodplains play an essential role in the processing and decomposition of organic matter and in the self-purification ability of rivers, largely due to the activity of bacteria. Knowledge about the composition of bacterial communities and its impact on organic-matter cycling is crucial for the understanding of ecological processes in river-floodplain systems. Particle-associated and free-living bacterial assemblages from the Danube River and various floodplain pools with different hydrological characteristics were investigated using terminal restriction fragment length polymorphism analysis. The particle-associated bacterial community exhibited a higher number of operational taxonomic units (OTUs) and was more heterogeneous in time and space than the free-living community. The temporal dynamics of the community structure were generally higher in isolated floodplain pools. The community structures of the river and the various floodplain pools, as well as those of the particle-associated and free-living bacteria, differed significantly. The compositional dynamics of the planktonic bacterial communities were related to changes in the algal biomass, temperature, and concentrations of organic and inorganic nutrients. The OTU richness of the free-living community was correlated with the concentration and origin of organic matter and the concentration of inorganic nutrients, while no correlation with the OTU richness of the particle-associated assemblage was found. Our results demonstrate the importance of the river-floodplain interactions and the influence of damming and regulation on the bacterial-community composition.     

Degradation of the herbicide bentazon as related to enzyme production by Phanerochaete chrysosporium in two solid substrate fermentation systems

Enzyme production and degradation of the herbicide bentazon by Phanerochaete chrysosporium growing on straw (solid substrate fermentation, SSF) and the effect of nitrogen and the hydraulic retention time (HRT) were studied using a small bioreactor and batch cultures. The best degradation of bentazon was obtained in the low nitrogen treatments, indicating participation of the ligninolytic system of the fungus. The treatments that degraded bentazon also had manganese peroxidase (MnP) activity, which seemed to be necessary for degradation. Pure MnP (with Mn(II) and H₂O₂) did not oxidize bentazon. However, in the presence of MnP, Mn(II) and Tween 80, bentazon was slowly oxidized in a H₂O₂-independent reaction. Bentazon was a substrate of pure lignin peroxidase (LiP) and was oxidized significantly faster (22,000–29,000 times) as compared to the MnP-Tween 80 system. Although LiP was a better enzyme for bentazon oxidation in vitro, its role in the SSF systems remains unclear since it was detected only in treatments with high nitrogen and high HRT where no degradation of bentazon occurred. Inhibition of LiP activity may be due to phenols and extractives present in the straw.     

Recurrent seasonal changes in bacterial growth efficiency,metabolism and community composition in coastal waters

The microbial response to environmental changes in coastal waters of the eastern Cantabrian Sea was explored for four years by analysing a broad set of environmental variables along with bacterial community metabolism and composition. A recurrent seasonal cycle emerged, consisting of two stable periods, characterized by low bacterial metabolic activity (winter) from October to March, and high bacterial metabolic activity (summer) from May to August. These two contrasting periods were linked by short transition periods in April (T_A) and September (T_S). The phylogenetic groups Alphaproteobacteria and Bacteroidetes were dominant during winter and summer respectively, and their recurrent alternation was mainly driven by the bloom of eukaryotic phytoplankton before T_A and the bloom of prokaryotic phytoplankton before T_S. Bacterial growth efficiency remained high and stable during the winter and summer periods but dropped during the two short transition periods. Our results suggest that bacterial growth efficiency should be considered a very resilient property that reflects different stages in the adaptation of the bacterial community composition to the environmental changes occurring throughout the seasonal cycle in this coastal ecosystem.     

Genetic and dermatoglyphic distances among Basque Valleys.

Palmar dermatoglyphics of a sample including 552 males and 701 females from 8 Basque valleys were analyzed. We studied the frequency of palmar pattern types and compared them using correspondence the frequency of palmar pattern types and compared them using correspondence analysis. The results of this comparative study show that there is diversity among valleys and also that this diversity depends on the trait and on sex. Genetic drift could explain this variability found in the Basque population.     

Residual Upper Arm Motor Function Primes Innervation of Paretic Forearm Muscles in Chronic Stroke after Brain-Machine Interface (BMI) Training

Background

Abnormal upper arm-forearm muscle synergies after stroke are poorly understood. We investigated whether upper arm function primes paralyzed forearm muscles in chronic stroke patients after Brain-Machine Interface (BMI)-based rehabilitation. Shaping upper arm-forearm muscle synergies may support individualized motor rehabilitation strategies.

Methods

Thirty-two chronic stroke patients with no active finger extensions were randomly assigned to experimental or sham groups and underwent daily BMI training followed by physiotherapy during four weeks. BMI sessions included desynchronization of ipsilesional brain activity and a robotic orthosis to move the paretic limb (experimental group, n = 16). In the sham group (n = 16) orthosis movements were random. Motor function was evaluated with electromyography (EMG) of forearm extensors, and upper arm and hand Fugl-Meyer assessment (FMA) scores. Patients performed distinct upper arm (e.g., shoulder flexion) and hand movements (finger extensions). Forearm EMG activity significantly higher during upper arm movements as compared to finger extensions was considered facilitation of forearm EMG activity. Intraclass correlation coefficient (ICC) was used to test inter-session reliability of facilitation of forearm EMG activity.

Results

Facilitation of forearm EMG activity ICC ranges from 0.52 to 0.83, indicating fair to high reliability before intervention in both limbs. Facilitation of forearm muscles is higher in the paretic as compared to the healthy limb (p<0.001). Upper arm FMA scores predict facilitation of forearm muscles after intervention in both groups (significant correlations ranged from R = 0.752, p = 0.002 to R = 0.779, p = 0.001), but only in the experimental group upper arm FMA scores predict changes in facilitation of forearm muscles after intervention (R = 0.709, p = 0.002; R = 0.827, p<0.001).

Conclusions

Residual upper arm motor function primes recruitment of paralyzed forearm muscles in chronic stroke patients and predicts changes in their recruitment after BMI training. This study suggests that changes in upper arm-forearm synergies contribute to stroke motor recovery, and provides candidacy guidelines for similar BMI-based clinical practice.     

Increased gene dosage of Ink4/Arf and p53 delays age‐associated central nervous system functional decline

The impairment of the activity of the brain is a major feature of aging, which coincides with a decrease in the function of neural stem cells. We have previously shown that an extra copy of regulated Ink4/Arf and p53 activity, in s‐Ink4/Arf/p53 mice, elongates lifespan and delays aging. In this work, we examined the physiology of the s‐Ink4/Arf/p53 brain with aging, focusing on the neural stem cell (NSC) population. We show that cells derived from old s‐Ink4/Arf/p53 mice display enhanced neurosphere formation and self‐renewal activity compared with wt controls. This correlates with augmented expression of Sox2, Sox9, Glast, Ascl1, and Ars2 NSC markers in the subventricular zone (SVZ) and in the subgranular zone of the dentate gyrus (DG) niches. Furthermore, aged s‐Ink4/Arf/p53 mice express higher levels of Doublecortin and PSA‐NCAM (neuroblasts) and NeuN (neurons) in the olfactory bulbs (OB) and DG, indicating increased neurogenesis in vivo. Finally, aged s‐Ink4/Arf/p53 mice present enhanced behavioral and neuromuscular coordination activity. Together, these findings demonstrate that increased but regulated Ink4/Arf and p53 activity ameliorates age‐related deterioration of the central nervous system activity required to maintain the stem cell pool, providing a mechanism not only for the extended lifespan but also for the health span of these mice.     

Particle‐association lifestyle is a phylogenetically conserved trait in bathypelagic prokaryotes

The free‐living (FL) and particle‐attached (PA) marine microbial communities have repeatedly been proved to differ in their diversity and composition in the photic ocean and also recently in the bathypelagic ocean at a global scale. However, although high taxonomic ranks exhibit preferences for a PA or FL mode of life, it remains poorly understood whether two clear lifestyles do exist and how these are distributed across the prokaryotic phylogeny. We studied the FL (<0.8 μm) and PA (0.8–20 μm) prokaryotes at 30 stations distributed worldwide within the bathypelagic oceanic realm (2150–4000 m depth) using high‐throughput sequencing of the small subunit ribosomal RNA gene (16S rRNA). A high proportion of the bathypelagic prokaryotes were mostly found either attached to particles or freely in the surrounding water but rarely in both types of environments. In particular, this trait was deeply conserved through their phylogeny, suggesting that the deep‐ocean particles and the surrounding water constitute two highly distinct niches and that transitions from one to the other have been rare at an evolutionary timescale. As a consequence, PA and FL communities had clear alpha‐ and beta‐diversity differences that exceeded the global‐scale geographical variation. Our study organizes the bathypelagic prokaryotic diversity into a reasonable number of ecologically coherent taxa regarding their association with particles, a first step for understanding which are the microbes responsible for the processing of the dissolved and particulate pools of organic matter that have a very different biogeochemical role in the deep ocean.     

On the Usage of Linear Regression Models to Reconstruct Limb Kinematics from Low Frequency EEG Signals

Several works have reported on the reconstruction of 2D/3D limb kinematics from low-frequency EEG signals using linear regression models based on positive correlation values between the recorded and the reconstructed trajectories. This paper describes the mathematical properties of the linear model and the correlation evaluation metric that may lead to a misinterpretation of the results of this type of decoders. Firstly, the use of a linear regression model to adjust the two temporal signals (EEG and velocity profiles) implies that the relevant component of the signal used for decoding (EEG) has to be in the same frequency range as the signal to be decoded (velocity profiles). Secondly, the use of a correlation to evaluate the fitting of two trajectories could lead to overly-optimistic results as this metric is invariant to scale. Also, the correlation has a non-linear nature that leads to higher values for sinus/cosinus-like signals at low frequencies. Analysis of these properties on the reconstruction results was carried out through an experiment performed in line with previous studies, where healthy participants executed predefined reaching movements of the hand in 3D space. While the correlations of limb velocity profiles reconstructed from low-frequency EEG were comparable to studies in this domain, a systematic statistical analysis revealed that these results were not above the chance level. The empirical chance level was estimated using random assignments of recorded velocity profiles and EEG signals, as well as combinations of randomly generated synthetic EEG with recorded velocity profiles and recorded EEG with randomly generated synthetic velocity profiles. The analysis shows that the positive correlation results in this experiment cannot be used as an indicator of successful trajectory reconstruction based on a neural correlate. Several directions are herein discussed to address the misinterpretation of results as well as the implications on previous invasive and non-invasive works.     

An Integrative Framework for Bayesian Variable Selection with Informative Priors for Identifying Genes and Pathways

The discovery of genetic or genomic markers plays a central role in the development of personalized medicine. A notable challenge exists when dealing with the high dimensionality of the data sets, as thousands of genes or millions of genetic variants are collected on a relatively small number of subjects. Traditional gene-wise selection methods using univariate analyses face difficulty to incorporate correlational, structural, or functional structures amongst the molecular measures. For microarray gene expression data, we first summarize solutions in dealing with ‘large p, small n’ problems, and then propose an integrative Bayesian variable selection (iBVS) framework for simultaneously identifying causal or marker genes and regulatory pathways. A novel partial least squares (PLS) g-prior for iBVS is developed to allow the incorporation of prior knowledge on gene-gene interactions or functional relationships. From the point view of systems biology, iBVS enables user to directly target the joint effects of multiple genes and pathways in a hierarchical modeling diagram to predict disease status or phenotype. The estimated posterior selection probabilities offer probabilitic and biological interpretations. Both simulated data and a set of microarray data in predicting stroke status are used in validating the performance of iBVS in a Probit model with binary outcomes. iBVS offers a general framework for effective discovery of various molecular biomarkers by combining data-based statistics and knowledge-based priors. Guidelines on making posterior inferences, determining Bayesian significance levels, and improving computational efficiencies are also discussed.