Imbalanced basal ganglia connectivity is associated with motor deficits and apathy in Huntington's disease

The gating of movement depends on activity within the cortico-striato-thalamic loops. Within these loops, emerging from the cells of the striatum, run two opponent pathways-the direct and indirect basal ganglia pathway. Both are complex and polysynaptic but the overall effect of activity within these pathways is thought to encourage and inhibit movement respectively. In Huntington's disease (HD), the preferential early loss of striatal neurons forming the indirect pathway is thought to lead to disinhibition giving rise to the characteristic motor features of the condition. But early HD is also associated with apathy, a loss of motivation and failure to engage in goal-directed movement. We hypothesised that in HD, motor signs and apathy may be selectively correlated with indirect and direct pathway dysfunction respectively. We used spectral dynamic casual modelling of resting state fMRI data to model effective connectivity in a model of these cortico-striatal pathways. We tested both of these hypotheses in vivo for the first time in a large cohort of patients with prodromal HD. Using an advanced approach at the group level by combining Parametric Empirical Bayes and Bayesian Model Reduction procedure to generate large number of competing models and compare them by using Bayesian model comparison. With this automated Bayesian approach, associations between clinical measures and connectivity parameters emerge de novo from the data. We found very strong evidence (posterior probability > 0.99) to support both of our hypotheses. Firstly, more severe motor signs in HD were associated with altered connectivity in the indirect pathway components of our model and, by comparison, loss of goal-direct behaviour or apathy, was associated with changes in the direct pathway component. The empirical evidence we provide here is demonstrates that imbalanced basal ganglia connectivity may play an important role in the pathogenesis of some of commonest and disabling features of HD and may have important implications for therapeutics

Humanising the mouse genome piece by piece

To better understand human health and disease, researchers create a wide variety of mouse models that carry human DNA. With recent advances in genome engineering, the targeted replacement of mouse genomic regions with orthologous human sequences has become increasingly viable, ranging from finely tuned humanisation of individual nucleotides and amino acids to the incorporation of many megabases of human DNA. Here, we examine emerging technologies for targeted genomic humanisation, we review the spectrum of existing genomically humanised mouse models and the insights such models have provided, and consider the lessons learned for designing such models in the future

Mycobacterial cultures contain cell size and density specific sub-populations of cells with significant differential susceptibility to antibiotics, oxidative and nitrite stress

The present study shows the existence of two specific sub-populations of Mycobacterium smegmatis and Mycobacterium tuberculosis cells differing in size and density, in the mid-log phase (MLP) cultures, with significant differential susceptibility to antibiotic, oxidative, and nitrite stress. One of these sub-populations (similar to 10% of the total population), contained short-sized cells (SCs) generated through highly-deviated asymmetric cell division (ACD) of normal/long-sized mother cells and symmetric cell divisions (SCD) of short-sized mother cells. The other sub-population (similar to 90% of the total population) contained normal/long-sized cells (NCs). The SCs were acid-fast stainable and heat-susceptible, and contained high density of membrane vesicles (MVs, known to be lipid-rich) on their surface, while the NCs possessed negligible density of MVs on the surface, as revealed by scanning and transmission electron microscopy. Percoll density gradient fractionation of MLP cultures showed the SCs-enriched fraction (SCF) at lower density (probably indicating lipid-richness) and the NCs-enriched fraction (NCF) at higher density of percoll fractions. While live cell imaging showed that the SCs and the NCs could grow and divide to form colony on agarose pads, the SCF, and NCF cells could independently regenerate MLP populations in liquid and solid media, indicating their full genomic content and population regeneration potential. CFU based assays showed the SCF cells to be significantly more susceptible than NCF cells to a range of concentrations of rifampicin and isoniazid (antibiotic stress), H2O2 (oxidative stress),and acidified NaNO2 (nitrite stress). Live cell imaging showed significantly higher susceptibility of the SCs of SC-NC sister daughter cell pairs, formed from highly-deviated ACD of normal/long-sized mother cells, to rifampicin and H2O2, as compared to the sister daughter NCs, irrespective of their comparable growth rates. The SC-SC sister daughter cell pairs, formed from the SCDs of short-sized mother cells and having comparable growth rates, always showed comparable stress-susceptibility. These observations and the presence of M. tuberculosis SCs and NCs in pulmonary tuberculosis patients' sputum earlier reported by us imply a physiological role for the SCs and the NCs under the stress conditions. The plausible reasons for the higher stress susceptibility of SCs and lower stress susceptibility of NCs are discussed

Ultrafast collinear scattering and carrier multiplication in graphene.

Graphene is emerging as a viable alternative to conventional optoelectronic, plasmonic and nanophotonic materials. The interaction of light with charge carriers creates an out-of-equilibrium distribution, which relaxes on an ultrafast timescale to a hot Fermi-Dirac distribution, that subsequently cools emitting phonons. Although the slower relaxation mechanisms have been extensively investigated, the initial stages still pose a challenge. Experimentally, they defy the resolution of most pump-probe setups, due to the extremely fast sub-100 fs carrier dynamics. Theoretically, massless Dirac fermions represent a novel many-body problem, fundamentally different from Schrödinger fermions. Here we combine pump-probe spectroscopy with a microscopic theory to investigate electron-electron interactions during the early stages of relaxation. We identify the mechanisms controlling the ultrafast dynamics, in particular the role of collinear scattering. This gives rise to Auger processes, including charge multiplication, which is key in photovoltage generation and photodetectors

ALS-related FUS mutations alter axon growth in motoneurons and affect HuD/ELAVL4 and FMRP activity

Mutations in the RNA-binding protein (RBP) FUS have been genetically associated with the motoneuron disease amyotrophic lateral sclerosis (ALS). Using both human induced pluripotent stem cells and mouse models, we found that FUS-ALS causative mutations affect the activity of two relevant RBPs with important roles in neuronal RNA metabolism: HuD/ELAVL4 and FMRP. Mechanistically, mutant FUS leads to upregulation of HuD protein levels through competition with FMRP for HuD mRNA 3’UTR binding. In turn, increased HuD levels overly stabilize the transcript levels of its targets, NRN1 and GAP43. As a consequence, mutant FUS motoneurons show increased axon branching and growth upon injury, which could be rescued by dampening NRN1 levels. Since similar phenotypes have been previously described in SOD1 and TDP-43 mutant models, increased axonal growth and branching might represent broad early events in the pathogenesis of ALS

Uniaxial strain in graphene by Raman spectroscopy: G peak splitting, Grüneisen parameters, and sample orientation

Graphene is the two-dimensional building block for carbon allotropes of every other dimensionality. Since its experimental discovery, graphene continues to attract enormous interest, in particular as a new kind of matter, in which electron transport is governed by a Dirac-like wave equation, and as a model system for studying electronic and phonon properties of other, more complex, graphitic materials[1-4]. Here, we uncover the constitutive relation of graphene and probe new physics of its optical phonons, by studying its Raman spectrum as a function of uniaxial strain. We find that the doubly degenerate E2g optical mode splits in two components, one polarized along the strain and the other perpendicular to it. This leads to the splitting of the G peak into two bands, which we call G+ and G-, by analogy with the effect of curvature on the nanotube G peak[5-7]. Both peaks red shift with increasing strain, and their splitting increases, in excellent agreement with first-principles calculations. Their relative intensities are found to depend on light polarization, which provides a useful tool to probe the graphene crystallographic orientation with respect to the strain. The singly degenerate 2D and 2D' bands also red shift, but do not split for small strains. We study the Gruneisen parameters for the phonons responsible for the G, D and D' peaks. These can be used to measure the amount of uniaxial or biaxial strain, providing a fundamental tool for nanoelectronics, where strain monitoring is of paramount importance[8, 9

ERABiLNet: enhanced residual attention with bidirectional long short-term memory

Alzheimer’s Disease (AD) causes slow death in brain cells due to shrinkage of brain cells which is more prevalent in older people. In most cases, the symptoms of AD are mistaken as age-related stresses. The most widely utilized method to detect AD is Magnetic Resonance Imaging (MRI). Along with Artificial Intelligence (AI) techniques, the efficacy of identifying diseases related to the brain has become easier. But, the identical phenotype makes it challenging to identify the disease from the neuro-images. Hence, a deep learning method to detect AD at the beginning stage is suggested in this work. The newly implemented “Enhanced Residual Attention with Bi-directional Long Short-Term Memory (Bi-LSTM) (ERABi-LNet)” is used in the detection phase to identify the AD from the MRI images. This model is used for enhancing the performance of the Alzheimer’s detection in scale of 2–5%, minimizing the error rates, increasing the balance of the model, so that the multi-class problems are supported. At first, MRI images are given to “Residual Attention Network (RAN)”, which is specially developed with three convolutional layers, namely atrous, dilated and Depth-Wise Separable (DWS), to obtain the relevant attributes. The most appropriate attributes are determined by these layers, and subjected to target-based fusion. Then the fused attributes are fed into the “Attention-based Bi-LSTM”. The final outcome is obtained from this unit. The detection efficiency based on median is 26.37% and accuracy is 97.367% obtained by tuning the parameters in the ERABi-LNet with the help of Modified Search and Rescue Operations (MCDMR-SRO). The obtained results are compared with ROA-ERABi-LNet, EOO-ERABi-LNet, GTBO-ERABi-LNet and SRO-ERABi-LNet respectively. The ERABi_LNet thus provides enhanced accuracy and other performance metrics compared to such deep learning models. The proposed method has the better sensitivity, specificity, F1-Score and False Positive Rate compared with all the above mentioned competing models with values such as 97.49%.97.84%,97.74% and 2.616 respective;y. This ensures that the model has better learning capabilities and provides lesser false positives with balanced prediction

Evaluation of the impact of high-resolution winds on the coastal waves

This study discusses the impact of high-resolution winds on the coastal waves and analyses the effectiveness of the high-resolution winds in recreating the fine-scale features along the coastal regions during the pre-monsoon season (March–May). The influence of the diurnal variation of winds on waves is studied for the Tamil Nadu coastal region using wind fields from weather research and forecast (WRF) (3 km) and European Centre for Medium-Range Weather Forecasts (ECMWF) (27.5 km). The improvement in the coastal forecast is then quantified with wave rider buoy observations. The high-resolution wind fields simulated fine-scale features like land–sea breeze events and showed good agreement with observation results. The error in the wave height and period is reduced by 8% and 46%, respectively, with the use of high-resolution forcing winds WRF over ECMWF, although the overestimation of wave energy on high frequencies due to overestimated WRF winds remains as a challenge in forecasting. The analysis also shows the importance of accurate wave forecast during a short-duration sudden wind (~12 m/s) occurrence in southern Tamil Nadu near Rameswaram during the pre-monsoon period. Low pressure forms over Tamil Nadu due to the land surface heating, resulting in a sudden increase of winds. High winds and steep waves which cause damage to the property of the coastal community near Rameswaram also were well simulated in the high-resolution forecast system with WRF winds

Local Optical Probe of Motion and Stress in a multilayer graphene NEMS

Nanoelectromechanical systems (NEMSs) are emerging nanoscale elements at the crossroads between mechanics, optics and electronics, with significant potential for actuation and sensing applications. The reduction of dimensions compared to their micronic counterparts brings new effects including sensitivity to very low mass, resonant frequencies in the radiofrequency range, mechanical non-linearities and observation of quantum mechanical effects. An important issue of NEMS is the understanding of fundamental physical properties conditioning dissipation mechanisms, known to limit mechanical quality factors and to induce aging due to material degradation. There is a need for detection methods tailored for these systems which allow probing motion and stress at the nanometer scale. Here, we show a non-invasive local optical probe for the quantitative measurement of motion and stress within a multilayer graphene NEMS provided by a combination of Fizeau interferences, Raman spectroscopy and electrostatically actuated mirror. Interferometry provides a calibrated measurement of the motion, resulting from an actuation ranging from a quasi-static load up to the mechanical resonance while Raman spectroscopy allows a purely spectral detection of mechanical resonance at the nanoscale. Such spectroscopic detection reveals the coupling between a strained nano-resonator and the energy of an inelastically scattered photon, and thus offers a new approach for optomechanics