Imaging mouse models of neurodegeneration using multi-parametric MRI

Alzheimer’s disease (AD) is a devastating condition characterised by significant cognitive impairment and memory loss. Transgenic mouse models are increasingly being used to further our knowledge of the cause and progression of AD, and identify new targets for therapeutic intervention. These mice permit the study of specific pathological hallmarks of the disease, including intracellular deposits of hyperphosphorylated tau protein and extracellular amyloid plaques. In order to characterise these transgenic mice, robust biomarkers are required to evaluate neurodegenerative changes and facilitate preclinical evaluation of emerging therapeutics. In this work, a platform for in vivo structural imaging of the rTg4510 mouse model of tauopathy was developed and optimised. This was combined with a range of other clinically relevant magnetic resonance imaging (MRI) biomarkers including: arterial spin labelling, diffusion tensor imaging and chemical exchange saturation transfer. These techniques were applied in a single time-point study of aged rTg4510 mice, as well as a longitudinal study to serially assess neurodegeneration in the same cohort of animals. Doxycycline was administered to a subset of rTg4510 mice to suppress the tau transgene; this novel intervention strategy permitted the evaluation of the sensitivity of MRI biomarkers to the accumulation and suppression of tau. Follow-up ex vivo scans were acquired in order to assess the sensitivity of in vivo structural MRI to the current preclinical gold standard. High resolution structural MRI, when used in conjunction with advanced computational analysis, yielded high sensitivity to pathological changes occurring in the rTg4510 mouse. Atrophy was reduced in animals treated with doxycycline. All other MRI biomarkers were able to discriminate between doxycycline-treated and untreated rTg4510 mice as well as wildtype controls, and provided insight into complimentary pathological mechanisms occurring within the disease process. In addition, this imaging protocol was applied to the J20 mouse model of familial AD. This mouse exhibits widespread plaque formation, enabling the study of amyloid-specific pathological changes. Atrophy and deficits in cerebral blood flow were observed; however, the changes occurring in this model were markedly less than those observed in the rTg4510 mouse. This study was expanded to investigate the early-onset AD observed in individuals with Down’s syndrome (DS) by breeding the J20 mouse with the Tc1 mouse model of DS, permitting the relationship between genetics and neurodegeneration to be dissected. This thesis demonstrates the application of in vivo multi-parametric MRI to mouse models of neurodegeneration. All techniques were sensitive to pathological changes occurring in the models, and may serve as important biomarkers in clinical studies of AD. In addition, in vivo multi-parametric MRI permits longitudinal studies of the same animal cohort. This experimental design produces more powerful results, whilst contributing to worldwide efforts to reduce animal usage with respect to the 3Rs principles

Attentional Modulation of Envelope-Following Responses at Lower (93–109 Hz) but Not Higher (217–233 Hz) Modulation Rates

Directing attention to sounds of different frequencies allows listeners to perceive a sound of interest, like a talker, in a mixture. Whether cortically generated frequency-specific attention affects responses as low as the auditory brainstem is currently unclear. Participants attended to either a high- or low-frequency tone stream, which was presented simultaneously and tagged with different amplitude modulation (AM) rates. In a replication design, we showed that envelope-following responses (EFRs) were modulated by attention only when the stimulus AM rate was slow enough for the auditory cortex to track—and not for stimuli with faster AM rates, which are thought to reflect ‘purer’ brainstem sources. Thus, we found no evidence of frequency-specific attentional modulation that can be confidently attributed to brainstem generators. The results demonstrate that different neural populations contribute to EFRs at higher and lower rates, compatible with cortical contributions at lower rates. The results further demonstrate that stimulus AM rate can alter conclusions of EFR studies.This work was supported by funding from the Canadian Institutes of Health Research (CIHR; Operating Grant: MOP 133450) and the Natural Sciences and Engineering Research Council of Canada (NSERC; Discovery Grant: 327429-2012). Authors R.P. Carlyon and H.E. Gockel were supported by intramural funding from the Medical Research Council [SUAG/007 RG91365]

Suspended two-dimensional electron gases in In₀.₇₅Ga₀.₂₅As quantum wells

We demonstrate that In0.75Ga0.25As quantum wells can be freely suspended without losing electrical quality when the epitaxial strain-relieving buffer layer is removed. In applied magnetic fields, non-dissipative behavior is observed in the conductivity, and a current induced breakdown of the quantum Hall effect shows a lower critical current in the suspended layers due to efficient thermal isolation compared to the non-suspended-control device. Beyond the critical current, background impurity scattering in the suspended two-dimensional channel regions dominates with stochastic, resonant-like features in the conductivity. This device fabrication scheme offers the potential for thermally isolated devices containing suspension-asymmetry-induced, high spin–orbit coupling strengths with reduced electron–phonon interaction behavior but without introducing high levels of disorder in the processing. This work was funded by EPSRC Grant Nos. EP/K004077/1 and EP/R029075/1, UK. We thank Professor Chris Ford for useful discussions

CDMS stands for Constrained Dark Matter Singlet

Motivated by the two candidate Dark Matter events observed by the CDMS experiment, we consider a Constrained Dark Matter Singlet (CDMS) model that, with no free parameters, predicts the DM mass and the DM direct cross section to be in the range weakly favored by CDMS.Comment: 6 pages, 2 figure

Gold nanoparticles enlighten the future of cancer theranostics

Development of multifunctional nanomaterials, one of the most interesting and advanced research areas in the field of nanotechnology, is anticipated to revolutionize cancer diagnosis and treatment. Gold nanoparticles (AuNPs) are now being widely utilized in bioimaging and phototherapy due to their tunable and highly sensitive optical and electronic properties (the surface plasmon resonance). As a new concept, termed “theranostics,” multifunctional AuNPs may contain diagnostic and therapeutic functions that can be integrated into one system, thereby simultaneously facilitating diagnosis and therapy and monitoring therapeutic responses. In this review, the important properties of AuNPs relevant to diagnostic and phototherapeutic applications such as structure, shape, optics, and surface chemistry are described. Barriers for translational development of theranostic AuNPs and recent advances in the application of AuNPs for cancer diagnosis, photothermal, and photodynamic therapy are discussed

Random-LTD: Random and Layerwise Token Dropping Brings Efficient Training for Large-scale Transformers

Large-scale transformer models have become the de-facto architectures for various machine learning applications, e.g., CV and NLP. However, those large models also introduce prohibitive training costs. To mitigate this issue, we propose a novel random and layerwise token dropping method (random-LTD), which skips the computation of a subset of the input tokens at all middle layers. Particularly, random-LTD achieves considerable speedups and comparable accuracy as the standard training baseline. Compared to other token dropping methods, random-LTD does not require (1) any importance score-based metrics, (2) any special token treatment (e.g., [CLS]), and (3) many layers in full sequence length training except the first and the last layers. Besides, a new LayerToken learning rate schedule is proposed for pretraining problems that resolve the heavy tuning requirement for our proposed training mechanism. Finally, we demonstrate that random-LTD can be applied to broader applications, including GPT and BERT pretraining as well as ViT and GPT finetuning tasks. Our results show that random-LTD can save about 33.3% theoretical compute cost and 25.6% wall-clock training time while achieving similar zero-shot evaluations on GPT-31.3B as compared to baseline.Comment: 22 page

Bis(triphenyl­stann­yl) thio­phene-2,5-dicarboxyl­ate

Mol­ecules of the title compound, [Sn2(C6H5)6(C6H2O4S)], lie on inversion centres with the central thio­phene ring disordered equally over two orientations. The carboxyl­ate groups are approximately coplanar with the thio­phene ring [dihedral angle = 4.0 (1)°] and the Sn—O bond distance of 2.058 (4) Å is comparable to that in related organotin carboxyl­ates

Time resolved particle dynamics in granular convection

We present an experimental study of the movement of individual particles in a layer of vertically shaken granular material. High-speed imaging allows us to investigate the motion of beads within one vibration period. This motion consists mainly of vertical jumps, and a global ordered drift. The analysis of the system movement as a whole reveals that the observed bifurcation in the flight time is not adequately described by the Inelastic Bouncing Ball Model. Near the bifurcation point, friction plays and important role, and the branches of the bifurcation do not diverge as the control parameter is increased. We quantify the friction of the beads against the walls, showing that this interaction is the underlying mechanism responsible for the dynamics of the flow observed near the lateral wall