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Research with childhood cancer has progressed greatly in recent years, resulting in much improved treatment that is more intensive. However, with this new treatment children often experience negative symptoms, and research shows that nausea is a symptom that most affects them. Pictorial support in person-centred care for children (PicPecc) is a digital picture-based tool for children who undergo treatment due to their cancer diagnosis and helps them more effectively communicate and self-report their symptoms and emotions. The aim of the study was to investigate children's experience of (i) using mHealth in nausea management and (ii) their acceptability of using an application (App). Semi-structured interviews were conducted with eight children aged five to fifteen years. Data were analysed with qualitative content analysis. The findings were presented in three categories 1) Communicating feelings, 2) Playfulness generated in motivation and 3) App adaptable to children's capabilities. Using an App contributed to new opportunities for the children to participate in their care. They experienced their treatment in different ways and used different strategies to manage and distract themselves from their symptoms. Using the PicPecc App can increase healthcare staff's understanding of how children experience nausea when they undergo chemotherapy.Theoretical considerations suggest that the strength of carbon nanotube (CNT) fibers be exceptional; however, their mechanical performance values are much lower than the theoretical values. To achieve macroscopic fibers with ultrahigh performance, we developed a method to form multidimensional nanostructures by coalescence of individual nanotubes. The highly aligned wet-spun fibers of single- or double-walled nanotube bundles were graphitized to induce nanotube collapse and multi-inner walled structures. These advanced nanostructures formed a network of interconnected, close-packed graphitic domains. Their near-perfect alignment and high longitudinal crystallinity that increased the shear strength between CNTs while retaining notable flexibility. The resulting fibers have an exceptional combination of high tensile strength (6.57 GPa), modulus (629 GPa), thermal conductivity (482 W/m·K), and electrical conductivity (2.2 MS/m), thereby overcoming the limits associated with conventional synthetic fibers.Electrophysiological studies in monkeys show that finger amputation triggers local remapping within the deprived primary somatosensory cortex (S1). Human neuroimaging research, however, shows persistent S1 representation of the missing hand's fingers, even decades after amputation. Here, we explore whether this apparent contradiction stems from underestimating the distributed peripheral and central representation of fingers in the hand map. Using pharmacological single-finger nerve block and 7-tesla neuroimaging, we first replicated previous accounts (electrophysiological and other) of local S1 remapping. Local blocking also triggered activity changes to nonblocked fingers across the entire hand area. Using methods exploiting interfinger representational overlap, however, we also show that the blocked finger representation remained persistent despite input loss. MS1943 Histone Methyltransferase inhibitor Computational modeling suggests that both local stability and global reorganization are driven by distributed processing underlying the topographic map, combined with homeostatic mechanisms. Our findings reveal complex interfinger representational features that play a key role in brain (re)organization, beyond (re)mapping.Recent evidence has demonstrated that during visual spatial attention sampling, neural activity and behavioral performance exhibit large fluctuations. To understand the origin of these fluctuations and their functional role, here, we introduce a mechanism based on the dynamical activity pattern (attention spotlight) emerging from neural circuit models in the transition regime between different dynamical states. This attention activity pattern with rich spatiotemporal dynamics flexibly samples from different stimulus locations, explaining many key aspects of temporal fluctuations such as variable theta oscillations of visual spatial attention. Moreover, the mechanism expands our understanding of how visual attention exploits spatially complex fluctuations characterized by superdiffusive motion in space and makes experimentally testable predictions. We further illustrate that attention sampling based on such spatiotemporal fluctuations provides profound functional advantages such as adaptive switching between exploitation and exploration activities and is particularly efficient at sampling natural scenes with multiple salient objects.We report high qubit coherence as well as low cross-talk and single-qubit gate errors in a superconducting circuit architecture that promises to be tileable to two-dimensional (2D) lattices of qubits. The architecture integrates an inductively shunted cavity enclosure into a design featuring nongalvanic out-of-plane control wiring and qubits and resonators fabricated on opposing sides of a substrate. The proof-of-principle device features four uncoupled transmon qubits and exhibits average energy relaxation times T1 = 149(38) μs, pure echoed dephasing times Tϕ,e = 189(34) μs, and single-qubit gate fidelities F = 99.982(4)% as measured by simultaneous randomized benchmarking. The 3D integrated nature of the control wiring means that qubits will remain addressable as the architecture is tiled to form larger qubit lattices. Band structure simulations are used to predict that the tiled enclosure will still provide a clean electromagnetic environment to enclosed qubits at arbitrary scale.Here, we report that the LynB splice variant of the Src-family kinase Lyn exerts a dominant immunosuppressive function in vivo, whereas the LynA isoform is uniquely required to restrain autoimmunity in female mice. We used CRISPR-Cas9 gene editing to constrain lyn splicing and expression, generating single-isoform LynA knockout (LynAKO) or LynBKO mice. Autoimmune disease in total LynKO mice is characterized by production of antinuclear antibodies, glomerulonephritis, impaired B cell development, and overabundance of activated B cells and proinflammatory myeloid cells. Expression of LynA or LynB alone uncoupled the developmental phenotype from the autoimmune disease B cell transitional populations were restored, but myeloid cells and differentiated B cells were dysregulated. These changes were isoform-specific, sexually dimorphic, and distinct from the complete LynKO. Despite the apparent differences in disease etiology and penetrance, loss of either LynA or LynB had the potential to induce severe autoimmune disease with parallels to human systemic lupus erythematosus (SLE).Coronary artery disease (CAD) remains the leading cause of death despite scientific advances. Elucidating shared CAD/pneumonia pathways may reveal novel insights regarding CAD pathways. We performed genome-wide pleiotropy analyses of CAD and pneumonia, examined the causal effects of the expression of genes near independently replicated SNPs and interacting genes with CAD and pneumonia, and tested interactions between disruptive coding mutations of each pleiotropic gene and smoking status on CAD and pneumonia risks. Identified pleiotropic SNPs were annotated to ADAMTS7 and IL6R. Increased ADAMTS7 expression across tissues consistently showed decreased risk for CAD and increased risk for pneumonia; increased IL6R expression showed increased risk for CAD and decreased risk for pneumonia. We similarly observed opposing CAD/pneumonia effects for NLRP3. Reduced ADAMTS7 expression conferred a reduced CAD risk without increased pneumonia risk only among never-smokers. Genetic immune-inflammatory axes of CAD linked to respiratory infections implicate ADAMTS7 and IL6R, and related genes.MicroRNAs (miRNAs) have been shown to hold prognostic value in acute myeloid leukemia (AML); however, the temporal dynamics of miRNA expression in AML are poorly understood. Using serial samples from a mouse model of AML to generate time-series miRNA sequencing data, we are the first to show that the miRNA transcriptome undergoes state-transition during AML initiation and progression. We modeled AML state-transition as a particle undergoing Brownian motion in a quasi-potential and validated the AML state-space and state-transition model to accurately predict time to AML in an independent cohort of mice. The critical points of the model provided a framework to align samples from mice that developed AML at different rates. Our mathematical approach allowed discovery of dynamic processes involved during AML development and, if translated to humans, has the potential to predict an individual's disease trajectory.The traditional view of neural computation in the cerebral cortex holds that sensory neurons are specialized, i.e., selective for certain dimensions of sensory stimuli. This view was challenged by evidence of contextual interactions between stimulus dimensions in which a neuron's response to one dimension strongly depends on other dimensions. Here, we use methods of mathematical modeling, psychophysics, and electrophysiology to address shortcomings of the traditional view. Using a model of a generic cortical circuit, we begin with the simple demonstration that cortical responses are always distributed among neurons, forming characteristic waveforms, which we call neural waves. When stimulated by patterned stimuli, circuit responses arise by interference of neural waves. Results of this process depend on interaction between stimulus dimensions. Comparison of modeled responses with responses of biological vision makes it clear that the framework of neural wave interference provides a useful alternative to the standard concept of neural computation.Using unique, new, matched UMETRICS data on people employed on research projects and Author-ity data on biomedical publications, this paper shows that National Institutes of Health funding stimulates research by supporting the teams that conduct it. While faculty-both principal investigators (PIs) and other faculty-and their productivity are heavily affected by funding, so are trainees and staff. The largest effects of funding on research output are ripple effects on publications that do not include PIs. While funders focus on research output from projects, they would be well advised to consider how funding ripples through the wide range of people, including trainees and staff, employed on projects.In superconductors, magnetic fields are quantized into discrete fluxons (flux quanta Φ0), made of microscopic circulating supercurrents. We introduce a multiterminal synapse network comprising a disordered array of superconducting loops with Josephson junctions. The loops can trap fluxons defining memory, while the junctions allow their movement between loops. Dynamics of fluxons through such a disordered system through a complex reconfigurable energy landscape represents brain-like spiking information flow. In this work, we experimentally demonstrate a three-loop network using YBa2Cu3O7 - δ-based superconducting loops and Josephson junctions, which exhibit stable memory configurations of trapped flux in loops that determine the rate of flow of fluxons through synaptic connections. The memory states are, in turn, affected by the applied input signals but can also be externally configured electrically through control current/feedback terminals. These results establish a previously unexplored, biologically similar architectural approach to neuromorphic computing that is scalable while dissipating energy of atto Joules/spike.