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A technique to reduce the probability of band-to-band tunneling for eliminating injected minority carriers in nano scale field-effect diode
On the limits of the intervention on complex systems guided by functional networks
Abstract Complex networks, and functional networks in particular, have become a standard tool to understand the structure and dynamics of real-world complex systems. One usually hidden assumption is that the structure of the reconstructed functional networks encodes useful information to guide interventions on the physical layer, when the latter is not known. We here test this assumption using a minimal model, simulating a propagation process in a physical network, and guiding interventions using node properties observed in the corresponding functional representation. We show how this approach becomes less optimal the more complex the topology is; up to becoming marginally better than choosing nodes at random in the real case of the European air transport network.
Synergistic effects of crystal habit and confining pressure on the compressive mechanical behavior of crystalline rock: a grain-based modeling analysis
An ovalbumin-based hydrogel loaded with dendrobium polysaccharide for promoting wound healing while reducing inflammations
A new modified incomprehensible but intelligible-in-time logics algorithm for modeling solid oxide fuel cell
Impacts of mechanized farmland transformation on ecological landscape patterns in hilly regions of Zhong County, China
Targeting the glioblastoma resection margin with locoregional nanotechnologies
Structural basis of voltage-dependent gating in BK channels
Abstract The allosteric communication between the pore domain, voltage sensors, and Ca2+ binding sites in the calcium- and voltage-activated K+ channel (BK) underlies its physiological role as the preeminent signal integrator in excitable systems. BK displays shallow voltage sensitivity with very fast gating charge kinetics, yet little is known about the molecular underpinnings of this distinctive behavior. Here, we explore the mechanistic basis of coupling between voltage-sensing domains (VSDs) and calcium sensors in Aplysia BK by locking the VSDs in their activated (R196Q and R199Q) and resting (R202Q) states, with or without calcium. Cryo-EM structures of these mutants reveal unique tilts at the S4 C-terminal end, together with large side-chain rotameric excursions of the gating charges. Notably, the VSD resting structure (R202Q) also revealed BK in its elusive, fully closed state, highlighting the reciprocal relation between calcium and voltage sensors. These structures provide a plausible path where voltage and Ca2+ binding couple energetically and define the conformation of the pore domain and, thus, BK’s full functional range.
Unsupervised learning of temporal regularities in visual cortical populations
Engineering a Proximity Biosensor via Constitutional Dynamic Chemistry
Abstract Affinity binding‐induced DNA assembly is a fundamental principle for designing proximity biosensors for sensitive and wash‐free protein detection and imaging. However, current design strategies for these biosensors face an intrinsic trade‐off between binding affinity and background signal. Here, we demonstrate that this intrinsic issue can be addressed by using constitutional dynamic chemistry (CDC) as a guiding principle in the rational design of proximity biosensors. As exists in a dynamic equilibrium, the constitutional dynamic network (CDN)‐based proximity biosensors can be adjusted to maximize the affinity to the target protein while minimizing non‐specific interactions that contribute to background signals. By further detecting the ratio of agonist to antagonist within the CDN, we also significantly improved assay robustness, enabling the sensitive detection of antibodies in complex matrices such as human serum. With the high affinity, low background, and high robustness, we anticipate that our CDN‐based design strategy will find wide applications in biosensor development. Our study also opens the possibility to engineer protein‐responsive synthetic systems with complex dynamic behaviors and functions.
The impact of remdesivir on renal and liver functions in severe COVID-19 patients with presence of viral load
Evaluating fungal pathogen resistance across the leaf economics spectrum using the generalist fungus Sclerotinia sclerotiorum
Use of bovine serum albumin might impair immunofluorescence signal in thick tissue samples
Abstract Significant progress in microscopic imaging techniques allowed transition from predominantly qualitative methods to a powerful tool for quantitative research, driven by improved instrumentation and computational power. Furthermore, previously limited to thin, laser-permeable tissue sections, imaging techniques have been revolutionized by the advent of tissue optical clearing. This innovation enables the visualization and quantitative analysis of entire organs and even whole bodies at cellular resolution. However, achieving high-quality imaging depends not only on the transparency of the tissue preparation but also on precise immunofluorescence labeling to ensure accurate signal detection and reliable study outcomes. In this study, we evaluated whether various reagents that are typically applied during the tissue blocking step prior to immunofluorescence staining affect the quality of the obtained image in thick and optically cleared samples. We demonstrate that the commonly employed tissue blocking step does not improve imaging conditions and even can substantially degrade fluorescence signal quality, particularly in large, optically cleared tissues such as whole mouse brain hemispheres.
Single-cell transcriptomics analysis reveals a disrupted NK-T cell interaction network in liver metastatic cancer
Experimental verification of position sensing for a magnetic coil via Fano resonance
Abstract Predicting the position of a magnetic noise source in the kilohertz/megahertz range is of interest in academia and importance in industries. We consider a system consisting of one transmitting and four receiving coils around a frequency of 10 MHz. The transmitting coil is assumed to be a magnetic noise source that needs to be found in our study. We theoretically and experimentally show that the position of the transmitting coil can be predicted using Fano resonance, i.e., the four receiving coils are strongly coupled with each other, and weakly coupled to the transmitting coil via magnetic fields, by employing supervised machine learning. A coupled mode theory is built to elucidate such magnetic resonance coupling among coils. The characteristics of the system are investigated by using a method-of-moment based electromagnetic simulator, with sufficiently large volume of scattering parameters for different positions of the transmitting coil. Measured spectra of scattering parameters reasonably agree with analytical and numerical results. Experimental results reveal that the position of the transmitting coil is predicted in a range of 0.4 m to 2 m for the distance and ± 60º for the angle, with resolutions of 0.048 m and 8.8º, respectively.