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At least 91 records · Page 5

A Route to Design Novel Functional Peptides by Applying a Denoising Diffusional Model to mRNA Display Libraries

In vitro directed evolution techniques, such as mRNA display, enable peptide ligand discovery and optimization. However, physical libraries that rely on a genetic code can only search a small fraction of sequence space due to inherent biases in the genetic code and experimental limitations. To address this challenge, denoising diffusion implicit models (DDIMs) are applied to generate novel peptide ligands against B‐cell lymphoma extra‐large (Bcl‐x L ), a key cancer target. Starting with high‐throughput sequencing data from previous selections, a DDIM is trained to produce novel sequences with high affinity binding. Experimental validation confirms that most generated sequences are functionally equivalent to the original library members for Bcl‐x L binding and demonstrated comparable binding kinetics and affinity relative to the wildtype and nearest original neighbors. Importantly, this approach generated rare sequences not easily accessible via mutation and directed evolution. These results indicate that DDIMs can complement and expand directed evolution data, efficiently exploring underrepresented regions of sequence space. This approach provides a broadly applicable framework for accelerating ligand discovery and optimizing molecular properties across diverse targets.

Qi, Pearl [Mork Family Department of Chemical Engi↗

The rate of microtubule breaking increases exponentially with curvature

Microtubules, cylindrical assemblies of tubulin proteins with a 25 nm diameter and micrometer lengths, are a central part of the cytoskeleton and also serve as building blocks for nanobiodevices. Microtubule breaking can result from the activity of severing enzymes and mechanical stress. Breaking can lead to a loss of structural integrity, or an increase in the numbers of microtubules. We observed breaking of taxol-stabilized microtubules in a gliding motility assay where microtubules are propelled by surface-adhered kinesin-1 motor proteins. We find that over 95% of all breaking events are associated with the strong bending following pinning events (where the leading tip of the microtubule becomes stuck). Furthermore, the breaking rate increased exponentially with increasing curvature. These observations are explained by a model accounting for the complex mechanochemistry of a microtubule. The presence of severing enzymes is not required to observe breaking at rates comparable to those measured previously in cells.

42 ENGINEERING↗

Strain-insensitive intrinsically stretchable transistors and circuits

An all-elastomer strain engineering approach, which uses patterned elastomer layers with tunable stiffnesses, can be used to create intrinsically stretchable transistor arrays with a device density of 340 transistors cm -2 and strain insensitivity of less than 5% performance variation when stretched to 100% strain. Intrinsically stretchable electronics can form intimate interfaces with the human body, creating devices that could be used to monitor physiological signals without constraining movement. However, mechanical strain invariably leads to the degradation of the electronic properties of the devices. Here we show that strain-insensitive intrinsically stretchable transistor arrays can be created using an all-elastomer strain engineering approach, in which the patterned elastomer layers with tunable stiffnesses are incorporated into the transistor structure. By varying the cross-linking density of the elastomers, areas of increased local stiffness are introduced, reducing strain on the active regions of the devices. This approach can be readily incorporated into existing fabrication processes, and we use it to create arrays with a device density of 340 transistors cm -2 and a strain insensitivity of less than 5% performance variation when stretched to 100% strain. We also show that it can be used to fabricate strain-insensitive circuit elements, including NOR gates, ring oscillators and high-gain amplifiers for the stable monitoring of electrophysiological signals.

42 ENGINEERING↗

Theoretical Analysis of Fractional Viscoelastic Flow in Circular Pipes: General Solutions

Fractional calculus is a relatively old yet emerging field of mathematics with the widest range of engineering and biomedical applications. Despite being an incredibly powerful tool, it, however, requires promotion in the engineering community. Rheology is undoubtedly one of the fields where fractional calculus has become an integral part of cutting-edge research. There exists extensive literature on the theoretical, experimental, and numerical treatment of various fractional viscoelastic flows in constraint geometries. However, the general theoretical approach that unites several most commonly used models is missing. Here we present exact analytical solutions for fractional viscoelastic flow in a circular pipe. We find velocity profiles and shear stresses for fractional Maxwell, Kelvin–Voigt, Zener, Poynting–Thomson, and Burgers models. The dynamics of these quantities are studied with respect to normalized pipe radius, fractional orders, and elastic moduli ratio. Three different types of behavior are identified: monotonic increase, resonant, and aperiodic oscillations. The models developed are applicable in the widest material range and allow for the alteration of the balance between viscous and elastic properties of the materials.

Gritsenko, Dmitry (ORCID:0000000248181512)↗

Magnetically responsive nanocultures for direct microbial assessment in soil environments

Cultivating microorganisms in native-like conditions is vital for bioprospecting and accessing now unculturable species. However, there remains a gap in scalable tools that can both mimic native microenvironments and enable targeted recovery of microbes from complex settings. Such approaches are essential to advance our understanding of microbial ecology, predict community functions, and discover previously unidentified biotherapeutics. We present magnetic nanocultures—a high-throughput microsystem for isolating and growing environmental microbes under near-native conditions. These nanoliter-scale bioreactors are encapsulated in semipermeable membranes that form magnetic polymeric microcapsules using iron oxide nanoparticles within polydimethylsiloxane-based shells. This design offers mechanical stability and magnetic actuation, enabling efficient retrieval from soil-like environments. The nanocultures are optimized for optical and biological properties to support microbial encapsulation, growth, and sorting. Our study demonstrates the feasibility of using magnetically responsive microenvironments to cultivate elusive microbes, offering a promising platform for bioprospecting previously uncultured or unknown microbial species.

Usman, Huda [Department of Chemical Engineering, C↗

Freestanding BaTiO 3 ‐Au Vertically Aligned Nanocomposite toward Flexible Multi‐Sensing Platform

Abstract Flexible and wearable sensors show enormous potential for personalized healthcare devices by real‐time monitoring of an individual's health. Typically, a single functional material is selected for one sensor to sense a particular physical signal while multiple materials will be selected for multi‐mode sensing. Vertically aligned nanocomposites (VANs) have recently demonstrated various material combinations and novel coupled multifunctionalities that are hard to achieve in any single‐phase material alone, including multiphase multiferroics, magneto‐optic coupling, and strong magnetic and optical anisotropy. Integrating these novel VANs into wearable sensors shows enormous potential in multi‐mode sensing owing to their multifunctional nature. In this work, the transfer of VANs onto polydimethylsiloxane as a novel flexible chemical and pressure sensor is demonstrated. For this demonstration, the classical BaTiO 3 ‐Au VAN with combined plasmonic and piezoelectric properties is used to demonstrate a multi‐sensing mechanism. A thin water‐soluble buffer of Sr 3 Al 2 O 6 serves as a buffer layer for the epitaxial growth and transfer process. The electrical output based on the piezoelectric responses and identifying 4‐mercaptobenzoic acid by surface‐enhanced Raman spectroscopy reveal great potential for free‐standing VANs in a wearable multifunctional sensing platform.

Tsai, Benson Kunhung [School of Materials Engineer↗

Physics-informed neural networks (PINNs) for fluid mechanics: a review

Despite the significant progress over the last 50 years in simulating flow problems using numerical discretization of the Navier–Stokes equations (NSE), we still cannot incorporate seamlessly noisy data into existing algorithms, mesh-generation is complex, and we cannot tackle high-dimensional problems governed by parametrized NSE. Moreover, solving inverse flow problems is often prohibitively expensive and requires complex and expensive formulations and new computer codes. Here, we review flow physics-informed learning, integrating seamlessly data and mathematical models, and implement them using physics-informed neural networks (PINNs). Here, we demonstrate the effectiveness of PINNs for inverse problems related to three-dimensional wake flows, supersonic flows, and biomedical flows.

42 ENGINEERING↗

Towards libraries of different ultrasmall amorphous silica cage topologies

Cage topology controlled at the nanometer length scale is expected to enable original functionalities, e.g., in catalysis and therapeutics. Cages are fundamental structural motifs of clathrates and their topological duals, Frank-Kasper phases, and are constituents of mesoporous silica frameworks. However, with one exception, they have not been synthesized as discrete particles. By varying reactant ratios of surfactant, oil, and silane, we report the discovery of 5(12)6(2) and 5(12)6(8) amorphous silica polyhedra, each coexisting with the previously identified 5(12) cage, using combined cryo-transmission electron microscopy (cryo-TEM) and single-particle reconstruction (SPR). Notably, the 5(12)6(8) polyhedron represents a topology not previously observed in mesoporous silica frameworks. Control over structural features is demonstrated, and insights into cage formation mechanisms are provided. Structural outcomes are summarized in a ternary morphology diagram alongside prior results, bridging serendipitous discovery and intentional design of silica cages displaying a level of control over silica polymerization rivaling nature.

Jang, Dong June [Department of Materials Science a↗

Mechanical and Light Activation of Materials for Chemical Production

Abstract Mechanical expansion and contraction of pores within photosynthetic organisms regulate a series of processes that are necessary to manage light absorption, control gas exchange, and regulate water loss. These pores, known as stoma, allow the plant to maximize photosynthetic output depending on environmental conditions such as light intensity, humidity, and temperature by actively changing the size of the stomal opening. Despite advances in artificial photosynthetic systems, little is known about the effect of such mechanical actuation in synthetic materials where chemical reactions occur. It is reported here on a hybrid hydrogel that combines light‐activated supramolecular polymers for superoxide production with thermal mechanical actuation of a covalent polymer. Superoxide production is important in organic synthesis and environmental remediation, and is a potential precursor to hydrogen peroxide liquid fuel. It is shown that the closing of pores in the hybrid hydrogel results in a substantial decrease in photocatalysis, but cycles of swollen and contracted states enhance photocatalysis. The observations motivate the development of biomimetic photosynthetic materials that integrate large scale motion and chemical reactions.

Đorđević, Luka [Department of Chemical Sciences Un↗

Technological Innovations from NASA

The challenge of human space exploration places demands on technology that push concepts and development to the leading edge. In biotechnology and biomedical equipment development, NASA science has been the seed for numerous innovations, many of which are in the commercial arena. The biotechnology effort has led to rational drug design, analytical equipment, and cell culture and tissue engineering strategies. Biomedical research and development has resulted in medical devices that enable diagnosis and treatment advances. NASA Biomedical developments are exemplified in the new laser light scattering analysis for cataracts, the axial flow left ventricular-assist device, non contact electrocardiography, and the guidance system for LASIK surgery. Many more developments are in progress. NASA will continue to advance technologies, incorporating new approaches from basic and applied research, nanotechnology, computational modeling, and database analyses.

Pellis, Neal R.↗

Dry electrodes with a printed cellulose–graphene ink for low-profile strain sensors in electromyography

Dihydrolevoglucosenone, commonly known as Cyrene, is a renewable and fully biodegradable cellulose-waste derived, environmentally friendly solvent, presenting a non-toxic alternative to N-methyl-2-pyrrolidone (NMP). Currently, solution-based processing of graphene and other similar van der Waals solids favor toxic solvents such as NMP, limiting their use for biosensing. However, with the use of Cyrene, bio-compatible printable devices are possible, and studies have already demonstrated its use in temperature and other biosensing methods through screen-printing. Screen-printing unfortunately often requires masks that constrain the minimum acquirable feature size to be above hundreds of centimeters and wastes material, adding to process complexity and cost. Conversely, inkjet-printing is an attractive alternative for the maskless patterning of hierarchically assembled structures, with micron length scales attainable. Graphene's high conductivity positions it ideally for long-wear sensors such as dry electrodes or respiration monitors. Here, we demonstrate the potential of Cyrene-based graphene inks through few-layer inkjet printing on flexible substrates for the first time, to produce non-toxic conductors toward a strain-mediated mechanism for biosensing, used to detect bodily motion for wearable electronics. The challenges overcome in this study include engineering ink chemistry and printing parameters such that Cyrene's relatively high viscosity compared to typical inkjet solvents, still allows for droplet ejection in a conventional material printer, yielding well-resolved clean line-edges in contrast to other solvents that exhibit diffuse line-edges possibly from stray droplets and ink-splashing. Temperature-dependent transport measurements on the inkjet-printed Cyrene-based graphene films showed the conductivity to be largely temperature-invariant but at lower temperatures below 100 K, conductivity decreased, likely as a result of increased inter-membrane separation arising from thermal contraction. Additionally, temperature-dependent Raman spectroscopy showed the red-shift in the G-band, 2D-band and D-band peaks, as temperature increased. As a result, by validating flexion motion detection of the proximal interphalangeal joint demonstrated in this study, our work is the first of its kind to successfully additively manufacture inkjet-printed Cyrene-based graphene strain sensors on flexible substrates for bio-sensing and wearables.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Optical information transfer through random unknown diffusers using electronic encoding and diffractive decoding

Free-space optical information transfer through diffusive media is critical in many applications, such as biomedical devices and optical communication, but remains challenging due to random, unknown perturbations in the optical path. We demonstrate an optical diffractive decoder with electronic encoding to accurately transfer the optical information of interest, corresponding to, e.g., any arbitrary input object or message, through unknown random phase diffusers along the optical path. This hybrid electronic-optical model, trained using supervised learning, comprises a convolutional neural network-based electronic encoder and successive passive diffractive layers that are jointly optimized. After their joint training using deep learning, our hybrid model can transfer optical information through unknown phase diffusers, demonstrating generalization to new random diffusers never seen before. The resulting electronic-encoder and optical-decoder model was experimentally validated using a 3D-printed diffractive network that axially spans <70λ, where λ = 0.75 mm is the illumination wavelength in the terahertz spectrum, carrying the desired optical information through random unknown diffusers. The presented framework can be physically scaled to operate at different parts of the electromagnetic spectrum, without retraining its components, and would offer low-power and compact solutions for optical information transfer in free space through unknown random diffusive media.

36 MATERIALS SCIENCE↗

Optics-Free Chip-Scale Intraoperative Imaging Using NIR-Excited Upconverting Nanoparticles

Here we present an optics-free CMOS image sensor that incorporates a novel time-gated dual-photodiode pixel design to allow filter- and lens-less image acquisition of near-infrared-excited (NIR-excited) upconverting nanoparticles. Recent biomedical advances have highlighted the benefits of NIR excitation, but NIR interaction with silicon has remained a challenge, even with high-performance optical blocking filters. Using a secondary diode and a dual-photodiode design, this sensor is able to remove the 100s of mV of NIR background on pixels and bring it down to single-digit mV level, nearing its noise floor of 2.2 mV rms, not achievable with any optical filter. Non-linear effects of background cancellation using the diode pair has been mitigated using an initial one-time pixel-level curve fitting and calibration in a post-processing setting. This imager comprises a highly linear 11 fF metal-oxide-metal (MOM) capacitor and includes integrated angle-selective gratings to reject oblique light and enhance sharpness. Each pixel also includes two distinct correlated double sampling schemes, to remove low frequency flicker noise and systematic offset in the datapath. We demonstrate the performance of this imager using pulsed NIR-excited upconverting nanoparticles on standard United-States-Air-Force (USAF) resolution targets and achieve an SNR of 15 dB, while keeping NIR background below 6 mV. This 36-by-80-pixel array measures only 2.3 mm by 4.8 mm and can be thinned down to 25 µm, allowing it to become surgically compatible with intraoperative instruments and equipment, while remaining optics-free.

42 ENGINEERING↗

Mondo: integrating disease terminology across communities

Precision medicine aims to enhance diagnosis, treatment, and prognosis by integrating multimodal data at the point of care. However, challenges arise due to the vast number of diseases, differing methods of classification, and conflicting terminological coding systems and practices used to represent molecular definitions of disease. This lack of interoperability artificially constrains the potential for diagnosis, clinical decision support, care outcome analysis, as well as data linkage across research domains to support the development or repurposing of therapeutics. There is a clear and pressing need for a unified system for managing disease entities⁠—including identifiers, synonyms, and definitions. To address these issues, we created the Mondo disease ontology—a community-driven, open-source, unified disease classification system that harmonizes diverse terminologies into a consistent, computable framework. Mondo integrates key medical and biomedical terminologies, including Online Mendelian Inheritance in Man (OMIM), Orphanet, Medical Subject Headings (MeSH), National Cancer Institute Thesaurus (NCIt), and more, to provide a comprehensive and accurate representation of disease concepts with fully provenanced and attributed links back to the sources. Mondo can be used as the handle for curation of gene–disease associations utilized in diagnostic applications, research applications such as computational phenotyping, and in clinical coding systems in clinical decision support by pointing the clinician to the numerous knowledge resources linked to the Mondo identifier. Mondo's community-centric approach, stewarded by the Monarch Initiative's expertise in ontologies, ensures that the ontology remains adaptable to the evolving needs of biomedical research and clinical communities, as well as the knowledge providers.

biomedical informatics↗