Burnettstorgaard8338

Drosophila flies are versatile animal models for the study of gene mutations in neuronal pathologies. Their small size allows performing in vivo Magic Angle Spinning (MAS) experiments to obtain high-resolution 1H nuclear magnetic resonance (NMR) spectra. Here, we use spatially-resolved 1H high-resolution MAS NMR to investigate in vivo metabolite contents in different segments of the fly body. A comparative study of metabolic changes was performed for three neurodegenerative disorders two cell-specific neuronal and glial models of Huntington disease (HD) and a model of glutamate excitotoxicity. It is shown that these pathologies are characterized by specific and sometimes anatomically localized variations in metabolite concentrations. In two cases, the modifications of 1H MAS NMR spectra localized in fly heads were significant enough to allow the creation of a predictive model.Breast cancer stem cells (BCSCs) are considered to be the root of breast cancer occurrence and progression. However, the characteristics and regulatory mechanisms of BCSCs metabolism have been poorly revealed, which hinders the development of metabolism-targeted treatment strategies for BCSCs elimination. Herein, we demonstrated that the downregulation of Caveolin-1 (Cav-1) usually occurred in BCSCs and was associated with a metabolic switch from mitochondrial respiration to aerobic glycolysis. Meanwhile, Cav-1 could inhibit the self-renewal capacity and aerobic glycolysis activity of BCSCs. Furthermore, Cav-1 loss was associated with accelerated mammary-ductal hyperplasia and mammary-tumor formation in transgenic mice, which was accompanied by enrichment and enhanced aerobic glycolysis activity of BCSCs. Mechanistically, Cav-1 could promote Von Hippel-Lindau (VHL)-mediated ubiquitination and degradation of c-Myc in BCSCs through the proteasome pathway. Notably, epithelial Cav-1 expression significantly correlated with a better overall survival and delayed onset age of breast cancer patients. Together, our work uncovers the characteristics and regulatory mechanisms of BCSCs metabolism and highlights Cav-1-targeted treatments as a promising strategy for BCSCs elimination.Comorbidities such as anemia or hypertension and physiological factors related to exertion can influence a patient's hemodynamics and increase the severity of many cardiovascular diseases. Observing and quantifying associations between these factors and hemodynamics can be difficult due to the multitude of co-existing conditions and blood flow parameters in real patient data. Machine learning-driven, physics-based simulations provide a means to understand how potentially correlated conditions may affect a particular patient. Here, we use a combination of machine learning and massively parallel computing to predict the effects of physiological factors on hemodynamics in patients with coarctation of the aorta. We first validated blood flow simulations against in vitro measurements in 3D-printed phantoms representing the patient's vasculature. We then investigated the effects of varying the degree of stenosis, blood flow rate, and viscosity on two diagnostic metrics - pressure gradient across the stenosis (ΔP) and wall shear stress (WSS) - by performing the largest simulation study to date of coarctation of the aorta (over 70 million compute hours). Using machine learning models trained on data from the simulations and validated on two independent datasets, we developed a framework to identify the minimal training set required to build a predictive model on a per-patient basis. We then used this model to accurately predict ΔP (mean absolute error within 1.18 mmHg) and WSS (mean absolute error within 0.99 Pa) for patients with this disease.An amendment to this paper has been published and can be accessed via a link at the top of the paper.Artificial Intelligence (AI) at the edge has become a hot subject of the recent technology-minded publications. The challenges related to IoT nodes gave rise to research on efficient hardware-based accelerators. In this context, analog memristor devices are crucial elements to efficiently perform the multiply-and-add (MAD) operations found in many AI algorithms. This is due to the ability of memristor devices to perform in-memory-computing (IMC) in a way that mimics the synapses in human brain. Here, we present a novel planar analog memristor, namely NeuroMem, that includes a partially reduced Graphene Oxide (prGO) thin film. The analog and non-volatile resistance switching of NeuroMem enable tuning it to any value within the RON and ROFF range. These two features make NeuroMem a potential candidate for emerging IMC applications such as inference engine for AI systems. Moreover, the prGO thin film of the memristor is patterned on a flexible substrate of Cyclic Olefin Copolymer (COC) using standard microfabrication techniques. This provides new opportunities for simple, flexible, and cost-effective fabrication of solution-based Graphene-based memristors. In addition to providing detailed electrical characterization of the device, a crossbar of the technology has been fabricated to demonstrate its ability to implement IMC for MAD operations targeting fully connected layer of Artificial Neural Network. This work is the first to report on the great potential of this technology for AI inference application especially for edge devices.With advances in tumour biology and immunology that continue to refine our understanding of cancer, therapies are now being developed to treat cancers on the basis of specific molecular alterations and markers of immune phenotypes that transcend specific tumour histologies. With the landmark approvals of pembrolizumab for the treatment of patients whose tumours have high microsatellite instability and larotrectinib and entrectinib for those harbouring NTRK fusions, a regulatory pathway has been created to facilitate the approval of histology-agnostic indications. Negative results presented in the past few years, however, highlight the intrinsic complexities faced by drug developers pursuing histology-agnostic therapeutic agents. When patient selection and statistical analysis involve multiple potentially heterogeneous histologies, guidance is needed to navigate the challenges posed by trial design. Additionally, as new therapeutic agents are tested and post-approval data become available, the regulatory framework for acting on these data requires further optimization. In this Review, we summarize the development and testing of approved histology-agnostic therapeutic agents and present data on other agents currently under development. Finally, we discuss the challenges intrinsic to histology-agnostic drug development in oncology, including biological, regulatory, design and statistical considerations.A bridge to surgery (BTS) after a colonic stent for obstructive colon cancer has not been accepted as a standard treatment strategy. Also, there is no consensus regarding the optimal time interval for BTS. We aimed to identify the optimal timing for BTS after stent placement to decrease the oncologic risk. We retrospectively collected data of 174 patients who underwent BTS after stent placement for stage II or III obstructive colon cancer from five hospitals. We divided the patients into three groups based on the time interval for BTS after stent placement within 7 days (Group 1), from 8 to 14 days (Group 2), and after 14 days (Group 3). The primary outcome was to compare the oncologic outcomes including overall survival (OS), disease-free survival (DFS), and recurrence rate (RR) among the three groups. Groups 1, 2, and 3 involved 75, 56, and 43 patients, respectively. Postoperative morbidity rates were 17.3%, 10.8%, and 9.3% in Groups 1, 2, and 3, respectively (P = 0.337). RRs were 16.0%, 35.7%, and 30.2% in Groups 1, 2, and 3, respectively (P = 0.029). In multivariate analysis, the time interval for BTS was an independent risk factor for DFS (P less then 0.001; HR, 14.463; 95% CI, 1.458-3.255) and OS (P = 0.027; HR, 4.917; 95% CI, 1.071-3.059). In conclusion, the perioperative short-term outcome was not affected by the time interval of BTS. However, elective surgery within 7 days after colonic stent might be suggested to balance the short-term benefits and long-term oncologic risks.An amendment to this paper has been published and can be accessed via a link at the top of the paper.Understanding the driving forces that control vole population dynamics requires identifying bacterial parasites hosted by the voles and describing their dynamics at the community level. To this end, we used high-throughput DNA sequencing to identify bacterial parasites in cyclic populations of montane water voles that exhibited a population outbreak and decline in 2014-2018. An unexpectedly large number of 155 Operational Taxonomic Units (OTUs) representing at least 13 genera in 11 families was detected. Individual bacterial richness was higher during declines, and vole body condition was lower. TL13-112 ic50 Richness as estimated by Chao2 at the local population scale did not exhibit clear seasonal or cycle phase-related patterns, but at the vole meta-population scale, exhibited seasonal and phase-related patterns. Moreover, bacterial OTUs that were detected in the low density phase were geographically widespread and detected earlier in the outbreak; some were associated with each other. Our results demonstrate the complexity of bacterial community patterns with regard to host density variations, and indicate that investigations about how parasites interact with host populations must be conducted at several temporal and spatial scales multiple times per year over multiple years, and at both local and long-distance dispersal scales for the host(s) under consideration.Twisted two-dimensional bilayer materials exhibit many exotic electronic phenomena. Manipulating the 'twist angle' between the two layers enables fine control of the electronic band structure, resulting in magic-angle flat-band superconductivity1,2, the formation of moiré excitons3-8 and interlayer magnetism9. However, there are limited demonstrations of such concepts for photons. Here we show how analogous principles, combined with extreme anisotropy, enable control and manipulation of the photonic dispersion of phonon polaritons in van der Waals bilayers. We experimentally observe tunable topological transitions from open (hyperbolic) to closed (elliptical) dispersion contours in bilayers of α-phase molybdenum trioxide (α-MoO3), arising when the rotation between the layers is at a photonic magic twist angle. These transitions are induced by polariton hybridization and are controlled by a topological quantity. At the transitions the bilayer dispersion flattens, exhibiting low-loss tunable polariton canalization and diffractionless propagation with a resolution of less than λ0/40, where λ0 is the free-space wavelength. Our findings extend twistronics10 and moiré physics to nanophotonics and polaritonics, with potential applications in nanoimaging, nanoscale light propagation, energy transfer and quantum physics.Magic-angle twisted bilayer graphene exhibits a variety of electronic states, including correlated insulators1-3, superconductors2-4 and topological phases3,5,6. Understanding the microscopic mechanisms responsible for these phases requires determination of the interplay between electron-electron interactions and quantum degeneracy (the latter is due to spin and valley degrees of freedom). Signatures of strong electron-electron correlations have been observed at partial fillings of the flat electronic bands in recent spectroscopic measurements7-10, and transport experiments have shown changes in the Landau level degeneracy at fillings corresponding to an integer number of electrons per moiré unit cell2-4. However, the interplay between interaction effects and the degeneracy of the system is currently unclear. Here we report a cascade of transitions in the spectroscopic properties of magic-angle twisted bilayer graphene as a function of electron filling, determined using high-resolution scanning tunnelling microscopy.