Viscosity Regulation of Chemically Simple Condensates.

This study investigates the viscosity and liquid-solid transition behavior of biomolecular condensates formed by polyarginine chains (Rx) of varying lengths and citric acid (CA) derivatives. By condensing Rx chains of various lengths with CA derivatives, we showed that the shorter Rx chains attenuate the high aggregation tendency of the longer chains when condensed with CA. A mixture of different Rx lengths exhibited uniform intracondensate distribution, while its mobility largely depended on the ratio of the longer Rx chain. Our findings demonstrate a simple method to modulate condensate properties by adjusting the composition of scaffold molecules, shedding light on the role of molecular composition in controlling condensate viscosity and transition dynamics. This research contributes to a deeper understanding of biomolecular condensation processes and offers insights into potential strategies for manipulating condensate properties for various applications, including in the fields of synthetic biology and disease therapeutics in the future.

Multi-Feature Automatic Extraction for Detecting Obstructive Sleep Apnea Based on Single-Lead Electrocardiography Signals.

Obstructive sleep apnea (OSA), a prevalent sleep disorder, is intimately associated with various other diseases, particularly cardiovascular conditions. The conventional diagnostic method, nocturnal polysomnography (PSG), despite its widespread use, faces challenges due to its high cost and prolonged duration. Recent developments in electrocardiogram-based diagnostic techniques have opened new avenues for addressing these challenges, although they often require a deep understanding of feature engineering. In this study, we introduce an innovative method for OSA classification that combines a composite deep convolutional neural network model with a multimodal strategy for automatic feature extraction. This approach involves transforming the original dataset into scalogram images that reflect heart rate variability attributes and Gramian angular field matrix images that reveal temporal characteristics, aiming to enhance the diversity and richness of data features. The model comprises automatic feature extraction and feature enhancement components and has been trained and validated on the PhysioNet Apnea-ECG database. The experimental results demonstrate the model's exceptional performance in diagnosing OSA, achieving an accuracy of 96.37%, a sensitivity of 94.67%, a specificity of 97.44%, and an AUC of 0.96. These outcomes underscore the potential of our proposed model as an efficient, accurate, and convenient tool for OSA diagnosis.

Randomly Disassembled Nanostructure for Wide Angle Light Extraction of Top-Emitting Quantum Dot Light-Emitting Diodes.

The quantum dot light-emitting diode (QLED) represents one of the strongest display technologies and has unique advantages like a shallow emission spectrum and superior performance based on the cumulative studies of state-of-the-art quantum dot (QD) synthesis and interfacial engineering. However, research on managing the device's light extraction has been lacking compared to the conventional LED field. Moreover, relevant studies on top-emitting QLEDs (TE-QLEDs) have been severely lacking compared to bottom-emitting QLEDs (BE-QLEDs). This paper demonstrates a novel light extraction structure called the randomly disassembled nanostructure (RaDiNa). The RaDiNa is formed by detaching polydimethylsiloxane (PDMS) film from a ZnO nanorod (ZnO NR) layer and laying it on top of the TE-QLED. The RaDiNa-attached TE-QLED shows significantly widened angular-dependent electroluminescence (EL) intensities over the pristine TE-QLED, confirming the effective light extraction capability of the RaDiNa layer. Consequently, the optimized RaDiNa-attached TE-QLED achieves enhanced external quantum efficiency (EQE) over the reference device by 60%. For systematic analyses, current-voltage-luminance (J-V-L) characteristics are investigated using scanning electron microscopy (SEM) and optical simulation based on COMSOL Multiphysics. It is believed that this study's results provide essential information for the commercialization of TE-QLEDs.

Catechol-Amyloid Interactions.

This review introduces multifaceted mutual interactions between molecules containing a catechol moiety and aggregation-prone proteins. The complex relationships between these two molecular species have previously been elucidated primarily in a unidirectional manner, as demonstrated in cases involving the development of catechol-based inhibitors for amyloid aggregation and the elucidation of the role of functional amyloid fibers in melanin biosynthesis. This review aims to consolidate scattered clues pertaining to catechol-based amyloid inhibitors, functional amyloid scaffold of melanin biosynthesis, and chemically designed peptide fibers for providing chemical insights into the role of the local three-dimensional orientation of functional groups in manifesting such interactions. These orientations may play crucial, yet undiscovered, roles in various supramolecular structures.

Designed Amyloid Fibers with Emergent Melanosomal Functions.

Short peptides designed to self-associate into amyloid fibers with metal ion-binding ability have been used to catalyze various types of chemical reactions. This manuscript demonstrates that one of these short-peptide fibers coordinated with CuII can exhibit melanosomal functions. The coordinated CuII and the amyloid structure itself are differentially functional in accelerating oxidative self-association of dopamine into melanin-like species and in regulating their material properties (e.g., water dispersion, morphology, and the density of unpaired electrons). The results have implications for the role of functional amyloids in melanin biosynthesis and for designing peptide-based supramolecular structures with various emergent functions.

Autocatalytic, bistable, oscillatory networks of biologically relevant organic reactions.

Networks of organic chemical reactions are important in life and probably played a central part in its origin. Network dynamics regulate cell division, circadian rhythms, nerve impulses and chemotaxis, and guide the development of organisms. Although out-of-equilibrium networks of chemical reactions have the potential to display emergent network dynamics such as spontaneous pattern formation, bistability and periodic oscillations, the principles that enable networks of organic reactions to develop complex behaviours are incompletely understood. Here we describe a network of biologically relevant organic reactions (amide formation, thiolate-thioester exchange, thiolate-disulfide interchange and conjugate addition) that displays bistability and oscillations in the concentrations of organic thiols and amides. Oscillations arise from the interaction between three subcomponents of the network: an autocatalytic cycle that generates thiols and amides from thioesters and dialkyl disulfides; a trigger that controls autocatalytic growth; and inhibitory processes that remove activating thiol species that are produced during the autocatalytic cycle. In contrast to previous studies that have demonstrated oscillations and bistability using highly evolved biomolecules (enzymes and DNA) or inorganic molecules of questionable biochemical relevance (for example, those used in Belousov-Zhabotinskii-type reactions), the organic molecules we use are relevant to metabolism and similar to those that might have existed on the early Earth. By using small organic molecules to build a network of organic reactions with autocatalytic, bistable and oscillatory behaviour, we identify principles that explain the ways in which dynamic networks relevant to life could have developed. Modifications of this network will clarify the influence of molecular structure on the dynamics of reaction networks, and may enable the design of biomimetic networks and of synthetic self-regulating and evolving chemical systems.

Task Migration and Scheduler for Mixed-Criticality Systems.

The interference between software components is increasing in safety-critical domains, such as autonomous driving. Low-criticality (LC) tasks, such as vehicle communication, may control high-criticality (HC) tasks, such as acceleration. In such cases, the LC task should also be considered as an HC task because the HC tasks relies on the LC task. However, the difficulty in guaranteeing these LC tasks is the catastrophic cost of computing resources, the electronic control unit in the domain of vehicles, required for every task. In this paper, we theoretically and practically provide safety-guaranteed and inexpensive scheduling for LC tasks by borrowing the computational power of neighbored systems in distributed systems, obviating the need for additional hardware components. As a result, our approach extended the schedulability of LC tasks without violating the HC tasks. Based on the deadline test, the compatibility of our approach with the task-level MC scheduler was higher than that of the system-level MC scheduler, such that the task-level had all dropped LC tasks recovered while the system-level only had 25.5% recovery. Conversely, from the worst-case measurement of violated HC tasks, the HC tasks were violated by the task-level MC scheduler more often than by the system-level MC scheduler, with 70.3% and 15.4% average response time overhead, respectively. In conclusion, under the condition that the HC task ratio has lower than 47% of the overall task systems at 80% of total utilization, the task-level approach with task migration has extensively higher sustainability on LC tasks.

Supramolecular Regulation of Polydopamine Formation by Amyloid Fibers.

Polydopamine (PD) and melanin species are chemically complex systems, the formation and properties of which are incompletely understood. Inspired by the role of functional amyloids in melanin biosynthesis, this paper examines the influences of the supramolecular structure of amyloids on oxidative polymerization of dopamine. Kinetic analyses on the formation of PD species in the presence of hen egg white lysozyme (HEWL) fibers or soluble HEWL revealed that both forms gave rise to the total quantity of PD species, but the rate of their formation could be accelerated only by the amyloid form. PD species formed with HEWL fibers showed a morphology of bundled fibers, whereas those with soluble HEWL had a mesh-like structure. Amyloid fibers of recombinant Pmel17 had properties similar to those of HEWL fibers in modulating PD formation. The results presented here suggest how nature designs functionality with an amyloid structure and can help understand and engineer chemistries of other functional amyloids.

Sintering Behavior of Copper Nanoparticle Ink by Laser in Air.

This paper presents a sintering technique using a laser in air which can provide heat for a few hundred milliseconds. In this study, a laser having a wavelength of 532 nm and a maximum-power output of 5 W was used. The effects of irradiated laser power at 104-282 W/cm² and sintering time of 50-330 milliseconds applied on spin-coated copper nanoparticle ink were investigated. The residual organic agent, oxidation, and specific resistance of the laser-sintered copper nanoparticle ink were characterized, and the sintering behavior was analyzed. For application, laser-sintered copper nanoparticle ink was confirmed to offer acceptable performance as a source and drain electrode in a thin-film transistor.

Neurite Guidance on Laser-Scribed Reduced Graphene Oxide.

This paper describes a one-step, chemical-free method to generate micropatterned in vitro neuronal networks on chemically unmodified reduced graphene oxide. The suggested method relies on infrared-based photothermal reduction of graphene oxide, which concurrently leads to the formation of submicrometer-scale surface roughness that promotes neuronal adhesion and guides neurite outgrowth. A commercially available laser source (LightScribe DVD drive) controlled by a computer software can be used to reduce graphene oxide (GO), and its repetitive scribing to a GO film brings about gradual increase and decrease in electrical conductivity and neurite guiding ability of the scribed regions, respectively. Our results also indicate that the observed adhesion-promoting and neurite guiding effect originate from the contrast in surface nanotopography, but not that in conductivity. This method is readily applicable to diverse graphene-based biomedical devices.

Nanotopography-Promoted Formation of Axon Collateral Branches of Hippocampal Neurons.

Axon collateral branches, as a key structural motif of neurons, allow neurons to integrate information from highly interconnected, divergent networks by establishing terminal boutons. Although physical cues are generally known to have a comprehensive range of effects on neuronal development, their involvement in axonal branching remains elusive. Herein, it is demonstrated that the nanopillar arrays significantly increase the number of axon collateral branches and also promote their growth. Immunostaining and biochemical analyses indicate that the physical interactions between the nanopillars and the neurons give rise to lateral filopodia at the axon shaft via cytoskeletal changes, leading to the formation of axonal branches. This report, demonstrates that nanotopography regulates axonal branching, and provides a guideline for the design of sophisticated neuron-based devices and scaffolds for neuro-engineering.

Accelerated Development of Hippocampal Neurons and Limited Adhesion of Astrocytes on Negatively Charged Surfaces.

This work examines the development of primary neurons and astrocytes on thoroughly controlled functional groups. Negatively charged surfaces presenting carboxylate (COO-) or sulfonate (SO3-) groups prove beneficial to neuronal behavior, in spite of their supposed repulsive electrostatic interactions with cellular membranes. The adhesion and survival of primary hippocampal neurons on negatively charged surfaces are comparable to or slightly better than those on positively charged (poly-d-lysine-coated) surfaces, and neuritogenesis and neurite outgrowth are accelerated on COO- and SO3- surfaces. Moreover, such favorable influences of the negatively charged surfaces are only seen in neurons but not for astrocytes. Our results indicate that the in vitro developmental behavior of primary hippocampal neurons is sophisticatedly modulated by angstrom-sized differences in chemical structure or the charge density of the surface. We believe that this work provides new implications for understanding neuron-material interfaces as well as for establishing new ways to fabricate neuro-active surfaces.

Tissue-based metabolic labeling of polysialic acids in living primary hippocampal neurons.

The posttranslational modification of neural cell-adhesion molecule (NCAM) with polysialic acid (PSA) and the spatiotemporal distribution of PSA-NCAM play an important role in the neuronal development. In this work, we developed a tissue-based strategy for metabolically incorporating an unnatural monosaccharide, peracetylated N-azidoacetyl-D-mannosamine, in the sialic acid biochemical pathway to present N-azidoacetyl sialic acid to PSA-NCAM. Although significant neurotoxicity was observed in the conventional metabolic labeling that used the dissociated neuron cells, neurotoxicity disappeared in this modified strategy, allowing for investigation of the temporal and spatial distributions of PSA in the primary hippocampal neurons. PSA-NCAM was synthesized and recycled continuously during neuronal development, and the two-color labeling showed that newly synthesized PSA-NCAMs were transported and inserted mainly to the growing neurites and not significantly to the cell body. This report suggests a reliable and cytocompatible method for in vitro analysis of glycans complementary to the conventional cell-based metabolic labeling for chemical glycobiology.

Anomalously Rapid Tunneling: Charge Transport across Self-Assembled Monolayers of Oligo(ethylene glycol).

This paper describes charge transport by tunneling across self-assembled monolayers (SAMs) of thiol-terminated derivatives of oligo(ethylene glycol) (HS(CH2CH2O)nCH3; HS(EG)nCH3); these SAMs are positioned between gold bottom electrodes and Ga2O3/EGaIn top electrodes. Comparison of the attenuation factor (ß of the simplified Simmons equation) across these SAMs with the corresponding value obtained with length-matched SAMs of oligophenyls (HS(Ph)nH) and n-alkanethiols (HS(CH2)nH) demonstrates that SAMs of oligo(ethylene glycol) have values of ß (ß(EG)n = 0.29 ± 0.02 natom-1 and ß = 0.24 ± 0.01 Å-1) indistinguishable from values for SAMs of oligophenyls (ß(Ph)n = 0.28 ± 0.03 Å-1), and significantly lower than those of SAMs of n-alkanethiolates (ß(CH2)n = 0.94 ± 0.02 natom-1 and 0.77 ± 0.03 Å-1). There are two possible origins for this low value of ß. The more probable involves hole tunneling by superexchange, which rationalizes the weak dependence of the rate of charge transport on the length of the molecules of HS(EG)nCH3 using interactions among the high-energy, occupied orbitals associated with the lone-pair electrons on oxygen. Based on this mechanism, SAMs of oligo(ethylene glycol)s are good conductors (by hole tunneling) but good insulators (by electron and/or hole drift conduction). This observation suggests SAMs derived from these or electronically similar molecules are a new class of electronic materials. A second but less probable mechanism for this unexpectedly low value of ß for SAMs of S(EG)nCH3 rests on the possibility of disorder in the SAM and a systematic discrepancy between different estimates of the thickness of these SAMs.

The influence of polydopamine coating on gold nanorods for laser desorption/ionization time-of-flight mass spectrometric analysis.

This paper examines the effect of polydopamine (PD) coating of gold nanorods (GNRs) on their performance as a matrix material for laser desorption/ionization time-of-flight mass spectrometry (LDI-TOF-MS) analysis. Bare GNRs and PD-coated GNRs (PD@GNRs) were utilized for LDI-TOF-MS analyses of small molecules and synthetic polymers, and the influences of PD-coating were mechanistically studied. Based on the results, we found that the PD-coating of GNRs suppressed the generation of undesired gold cluster ions, enhanced photothermal conversion and the LDI-TOF-MS efficiency, and expanded the working molecular weight range.

Privacy-Preserving Electrocardiogram Monitoring for Intelligent Arrhythmia Detection.

Long-term electrocardiogram (ECG) monitoring, as a representative application of cyber-physical systems, facilitates the early detection of arrhythmia. A considerable number of previous studies has explored monitoring techniques and the automated analysis of sensing data. However, ensuring patient privacy or confidentiality has not been a primary concern in ECG monitoring. First, we propose an intelligent heart monitoring system, which involves a patient-worn ECG sensor (e.g., a smartphone) and a remote monitoring station, as well as a decision support server that interconnects these components. The decision support server analyzes the heart activity, using the Pan-Tompkins algorithm to detect heartbeats and a decision tree to classify them. Our system protects sensing data and user privacy, which is an essential attribute of dependability, by adopting signal scrambling and anonymous identity schemes. We also employ a public key cryptosystem to enable secure communication between the entities. Simulations using data from the MIT-BIH arrhythmia database demonstrate that our system achieves a 95.74% success rate in heartbeat detection and almost a 96.63% accuracy in heartbeat classification, while successfully preserving privacy and securing communications among the involved entities.

Axon-First Neuritogenesis on Vertical Nanowires.

In this work, we report that high-density, vertically grown silicon nanowires (vg-SiNWs) direct a new in vitro developmental pathway of primary hippocampal neurons. Neurons on vg-SiNWs formed a single, extremely elongated major neurite earlier than minor neurites, which led to accelerated polarization. Additionally, the development of lamellipodia, which generally occurs on 2D culture coverslips, was absent on vg-SiNWs. The results indicate that surface topography is an important factor that influences neuronal development and also provide implications for the role of topography in neuronal development in vivo.

Cascade Classification with Adaptive Feature Extraction for Arrhythmia Detection.

Detecting arrhythmia from ECG data is now feasible on mobile devices, but in this environment it is necessary to trade computational efficiency against accuracy. We propose an adaptive strategy for feature extraction that only considers normalized beat morphology features when running in a resource-constrained environment; but in a high-performance environment it takes account of a wider range of ECG features. This process is augmented by a cascaded random forest classifier. Experiments on data from the MIT-BIH Arrhythmia Database showed classification accuracies from 96.59% to 98.51%, which are comparable to state-of-the art methods.

Water-Restructuring Mutations Can Reverse the Thermodynamic Signature of Ligand Binding to Human Carbonic Anhydrase.

This study uses mutants of human carbonic anhydrase (HCAII) to examine how changes in the organization of water within a binding pocket can alter the thermodynamics of protein-ligand association. Results from calorimetric, crystallographic, and theoretical analyses suggest that most mutations strengthen networks of water-mediated hydrogen bonds and reduce binding affinity by increasing the enthalpic cost and, to a lesser extent, the entropic benefit of rearranging those networks during binding. The organization of water within a binding pocket can thus determine whether the hydrophobic interactions in which it engages are enthalpy-driven or entropy-driven. Our findings highlight a possible asymmetry in protein-ligand association by suggesting that, within the confines of the binding pocket of HCAII, binding events associated with enthalpically favorable rearrangements of water are stronger than those associated with entropically favorable ones.

Tetrazine ligation for chemical proteomics.

Determining small molecule-target protein interaction is essential for the chemical proteomics. One of the most important keys to explore biological system in chemical proteomics field is finding first-class molecular tools. Chemical probes can provide great spatiotemporal control to elucidate biological functions of proteins as well as for interrogating biological pathways. The invention of bioorthogonal chemistry has revolutionized the field of chemical biology by providing superior chemical tools and has been widely used for investigating the dynamics and function of biomolecules in live condition. Among 20 different bioorthogonal reactions, tetrazine ligation has been spotlighted as the most advanced bioorthogonal chemistry because of their extremely faster kinetics and higher specificity than others. Therefore, tetrazine ligation has a tremendous potential to enhance the proteomic research. This review highlights the current status of tetrazine ligation reaction as a molecular tool for the chemical proteomics.