Freeform Fabrication of Biological Scaffolds by Projection Photopolymerization

This article presents a micro-manufacturing method for direct, projection printing of 3- dimensional (3D) scaffolds for applications in the field of tissue engineering by using a digital micro-mirror-array device (DMD) in a layer-by-layer process. Multi-layered scaffolds are microfabricated using curable materials through an ultraviolet (UV) photopolymerization process. The pre-patterned UV light is projected onto the photocurable polymer solution by creating the “photomask” design with graphic software. Poly (ethylene glycol) diacrylate (PEGDA), is mixed with a small amount of dye (0.3 wt %) to enhance the fabrication resolution of the scaffold. The DMD fabrication system is equipped with a purging mechanism to prevent the accumulation of oligomer, which could interfere with the feature resolution of previously polymerized layers. The surfaces of the pre-designed, multi-layered scaffold are covalently conjugated with fibronectin for efficient cellular attachment. Our results show that murine marrow-derived progenitor cells successfully attached to fibronectin-modified scaffolds.Mechanical Engineerin

Fabrication of Nanoimprinting Molds with Acrylic Polymer by Two-Photon Polymerization

We demonstrate the plausibility of making low-cost nanoimprinting molds with acrylic polymer using femtosecond-laser-induced two-photon polymerization (TPP) technique. A Ti:sapphire femtosecond laser was used to induce TPP in dipentaerythritol pentaacrylate to make nanostructures, the nanoimprinting mold, on pretreated glass substrate. A layer of fluoro-silane was then grown on the surface of the mold to promote the release of the mold after imprinting. To test the imprinting capacity of the mold, poly (ethylene glycol) diacrylate was patterned by the mold and the results were analyzed by a scanning electron microscope (SEM).Mechanical Engineerin

A Robotic Visual Grasping Design: Rethinking Convolution Neural Network with High-Resolutions

High-resolution representations are important for vision-based robotic grasping problems. Existing works generally encode the input images into low-resolution representations via sub-networks and then recover high-resolution representations. This will lose spatial information, and errors introduced by the decoder will be more serious when multiple types of objects are considered or objects are far away from the camera. To address these issues, we revisit the design paradigm of CNN for robotic perception tasks. We demonstrate that using parallel branches as opposed to serial stacked convolutional layers will be a more powerful design for robotic visual grasping tasks. In particular, guidelines of neural network design are provided for robotic perception tasks, e.g., high-resolution representation and lightweight design, which respond to the challenges in different manipulation scenarios. We then develop a novel grasping visual architecture referred to as HRG-Net, a parallel-branch structure that always maintains a high-resolution representation and repeatedly exchanges information across resolutions. Extensive experiments validate that these two designs can effectively enhance the accuracy of visual-based grasping and accelerate network training. We show a series of comparative experiments in real physical environments at Youtube: https://youtu.be/Jhlsp-xzHFY

Lightweight Neural Path Planning

Learning-based path planning is becoming a promising robot navigation methodology due to its adaptability to various environments. However, the expensive computing and storage associated with networks impose significant challenges for their deployment on low-cost robots. Motivated by this practical challenge, we develop a lightweight neural path planning architecture with a dual input network and a hybrid sampler for resource-constrained robotic systems. Our architecture is designed with efficient task feature extraction and fusion modules to translate the given planning instance into a guidance map. The hybrid sampler is then applied to restrict the planning within the prospective regions indicated by the guide map. To enable the network training, we further construct a publicly available dataset with various successful planning instances. Numerical simulations and physical experiments demonstrate that, compared with baseline approaches, our approach has nearly an order of magnitude fewer model size and five times lower computational while achieving promising performance. Besides, our approach can also accelerate the planning convergence process with fewer planning iterations compared to sample-based methods.Comment: 8 page

Selective axonal growth of embryonic hippocampal neurons according to topographic features of various sizes and shapes

David Y Fozdar1*, Jae Y Lee2*, Christine E Schmidt2–6, Shaochen Chen1,3–5,7,1Departments of Mechanical Engineering, 2Chemical Engineering, 3Biomedical Engineering; 4Center for Nano Molecular Science and Technology; 5Texas Materials Institute; 6Institute of Neuroscience; 7Microelectronics Research Center, The University of Texas at Austin, Austin, TX, USA *Contributed equally to this workPurpose: Understanding how surface features influence the establishment and outgrowth of the axon of developing neurons at the single cell level may aid in designing implantable scaffolds for the regeneration of damaged nerves. Past studies have shown that micropatterned ridge-groove structures not only instigate axon polarization, alignment, and extension, but are also preferred over smooth surfaces and even neurotrophic ligands.Methods: Here, we performed axonal-outgrowth competition assays using a proprietary four-quadrant topography grid to determine the capacity of various micropatterned topographies to act as stimuli sequestering axon extension. Each topography in the grid consisted of an array of microscale (approximately 2 µm) or submicroscale (approximately 300 nm) holes or lines with variable dimensions. Individual rat embryonic hippocampal cells were positioned either between two juxtaposing topographies or at the borders of individual topographies juxtaposing unpatterned smooth surface, cultured for 24 hours, and analyzed with respect to axonal selection using conventional imaging techniques.Results: Topography was found to influence axon formation and extension relative to smooth surface, and the distance of neurons relative to topography was found to impact whether the topography could serve as an effective cue. Neurons were also found to prefer submicroscale over microscale features and holes over lines for a given feature size.Conclusion: The results suggest that implementing physical cues of various shapes and sizes on nerve guidance conduits and other advanced biomaterial scaffolds could help stimulate axon regeneration.Keywords: axon guidance, micropatterning, polarization, surface topography, tissue engineerin

TODE-Trans: Transparent Object Depth Estimation with Transformer

Transparent objects are widely used in industrial automation and daily life. However, robust visual recognition and perception of transparent objects have always been a major challenge. Currently, most commercial-grade depth cameras are still not good at sensing the surfaces of transparent objects due to the refraction and reflection of light. In this work, we present a transformer-based transparent object depth estimation approach from a single RGB-D input. We observe that the global characteristics of the transformer make it easier to extract contextual information to perform depth estimation of transparent areas. In addition, to better enhance the fine-grained features, a feature fusion module (FFM) is designed to assist coherent prediction. Our empirical evidence demonstrates that our model delivers significant improvements in recent popular datasets, e.g., 25% gain on RMSE and 21% gain on REL compared to previous state-of-the-art convolutional-based counterparts in ClearGrasp dataset. Extensive results show that our transformer-based model enables better aggregation of the object's RGB and inaccurate depth information to obtain a better depth representation. Our code and the pre-trained model will be available at https://github.com/yuchendoudou/TODE.Comment: Submitted to ICRA202

Rotating optical catheter tip for optical coherence tomography

The present invention relates to a rotating catheter tip for optical coherence tomography based on the use of an optical fiber that does not rotate, that is enclosed in a catheter, which has a tip rotates under the influence of a fluid drive system to redirect light from the fiber to a surrounding vessel and the light reflected or backscattered from the vessel back to the optical fiber.Board of Regents, University of Texas Syste

COVID-19 vaccines based on viral nanoparticles displaying a conserved B-cell epitope show potent immunogenicity and a long-lasting antibody response

The COVID-19 pandemic caused by SARS-CoV-2 sparked intensive research into the development of effective vaccines, 50 of which have been approved thus far, including the novel mRNA-based vaccines developed by Pfizer and Moderna. Although limiting the severity of the disease, the mRNA-based vaccines presented drawbacks, such as the cold chain requirement. Moreover, antibody levels generated by these vaccines decline significantly after 6 months. These vaccines deliver mRNA encoding the full-length spike (S) glycoprotein of SARS-CoV-2, but must be updated as new strains and variants of concern emerge, creating a demand for adjusted formulations and booster campaigns. To overcome these challenges, we have developed COVID-19 vaccine candidates based on the highly conserved SARS CoV-2, 809-826 B-cell peptide epitope (denoted 826) conjugated to cowpea mosaic virus (CPMV) nanoparticles and bacteriophage Qβ virus-like particles, both platforms have exceptional thermal stability and facilitate epitope delivery with inbuilt adjuvant activity. We evaluated two administration methods: subcutaneous injection and an implantable polymeric scaffold. Mice received a prime–boost regimen of 100 μg per dose (2 weeks apart) or a single dose of 200 μg administered as a liquid formulation, or a polymer implant. Antibody titers were evaluated longitudinally over 50 weeks. The vaccine candidates generally elicited an early Th2-biased immune response, which stimulates the production of SARS-CoV-2 neutralizing antibodies, followed by a switch to a Th1-biased response for most formulations. Exceptionally, vaccine candidate 826-CPMV (administered as prime-boost, soluble injection) elicited a balanced Th1/Th2 immune response, which is necessary to prevent pulmonary immunopathology associated with Th2 bias extremes. While the Qβ-based vaccine elicited overall higher antibody titers, the CPMV-induced antibodies had higher avidity. Regardless of the administration route and formulation, our vaccine candidates maintained high antibody titers for more than 50 weeks, confirming a potent and durable immune response against SARS-CoV-2 even after a single dose

Extraordinary Transmission and Enhanced Emission with Metallic Gratings Having Converging-Diverging Channels

Transmission metallic gratings having the shape of converging-diverging channel (CDC) give an extra degree of freedom to exhibit enhanced transmission resonances. By varying the gap size at the throat of CDC, the spectral locations of the transmission resonance bands can be shifted close to each other and have high transmittance in a very narrow energy band. Hence, the CDC shape metallic gratings can lead to almost perfect transmittance for any desired wavelength by carefully optimizing the metallic material, gap at the throat of CDC, and grating parameters. In addition, a cavity surrounded by the CDC shaped metallic grating and a one-dimensional (1D) photonic crystal (PhC) can lead to an enhanced emission with properties similar to a laser. The large coherence length of the emission is achieved by exploiting the coherence properties of the surface waves on the gratings and PhC. The new multilayer structure can attain the spectral and directional control of emission with only p-polarization. The resonance condition inside the cavity is extremely sensitive to the wavelength, which would then lead to high emission in a very narrow wavelength band. Such simple 1D multilayer structure should be easy to fabricate and have applications in photonic circuits, thermophotovoltaics, and potentially in energy efficient incandescent sources

3D-Printed Artificial Microfish

Hydrogel microfish featuring biomimetic structures, locomotive capabilities, and functionalized nanoparticles are engineered using a rapid 3D printing platform: microscale continuous ­optical printing (μCOP). The 3D-printed ­microfish exhibit chemically powered and magnetically guided propulsion, as well as highly efficient detoxification capabilities that highlight the technical versatility of this platform for engineering advanced functional microswimmers for diverse biomedical applications