Versatile Optical Imaging Technique for Dynamic Monitoring and Quantitative Analysis in Tissue Engineering

Department of Biomedical EngineeringMany researches in the tissue engineering are investigating the development of technologies that have covered a broad range of applications and closely associated with the tissue regeneration and replacement of lost or damaged tissues as well as tissue manipulation. However, there are challenges regarding monitoring and assessing outcomes to analyze a variety of morphological and structural changes in tissue engineering applications. Most tissue engineering studies have utilized histopathological techniques for morphological analysis and evaluation of the tissues. Although the conventional methods provided a high definition and clear distinction under optical microscopy, it has still limitations in the visualization of tissue constructs without destruction of the tissues. Also, these methods have not allowed a volumetric assessment and functional information. Due to the destructive process and limited information in a two-dimensional approach, the conventional methods were difficult not only to analyze the specimens at continuous time points but also to compare inconsistencies of the results between different samples. For these reasons, there are clear needs for the development of advanced optical imaging techniques available for non-invasive and consistent observation and quantitative analysis in tissue engineering applications. Optical coherence tomography (OCT) has emerged as appropriate candidate for studying tissue morphology dynamically and quantitatively. OCT equips optimal imaging characteristics for dynamic monitoring because it offers cross-sectional, high-resolution, real-time tissue imaging in a non-invasive manner. Unlike most optical imaging techniques, OCT does not require any contrast agent or labeling process even it provides a deep penetration depth of about 2 mm in the tissue. Here, we utilized OCT technique to carry out application for the tissue engineering research ranging from the observation of biological tissues, dynamic monitoring, and quantitative analysis, as well as fabrication of image-guided engineered tissue. In the chapter 2, we utilized 3D OCT imaging to observe the tissue regeneration after laser irradiation, epidermal biopsy, and skin incision in in vitro and in vivo skin model. We utilized OCT system to monitor and analyze the wound recovery process after laser irradiation on the engineered skin. Also, we presented a quantitative evaluation of drug efficiency that affect the wound recovery on the engineered skin model after epidermal biopsy. Next, we analyzed quantitatively a recovery process of the wound width and depth in skin incised rat model in vivo with tissue adhesives treatment under the OCT monitoring. In the chapter 3, we utilized optical coherence microscopy (OCM) imaging modality to observe and quantitatively analyze the morphological changes of biological tissue in subcellular level. We introduced depth trajectory-tracking technique to acquire homogenous quality OCM images regardless of the height difference of the sample surface. Also, we developed the serial block-face OCM (SB-OCM) system to acquire the whole tissue information by repeating tissue sectioning and image acquisition using the serial block-face imaging technique. In the chapter 4, we developed the hand-held probe based portable OCT system for convenience in human target studies. We monitored and quantitatively analyzed various changes in the human skin using the hand-held probe based portable OCT system. Especially, we studied quantitative analysis of human skin wrinkle in terms of depth and volume as well as roughness parameters in comparison with conventional platforms. In the chapter 5, we suggested the feasibility to fabricate the engineered tissue based on a volumetric information of optical imaging. Here, we studied a fabrication of wrinkle mimicked engineered skin for anti-aging assessment and a protocol of imaging guided personalized engineered cornea for cornea transplantation. In conclusion, we confirmed that OCT system was able to provide various quantitative information from the biological tissues by its advantages such as high-resolution, non-invasive, label-free, deep penetration depth with real-time imaging. These characteristics of OCT imaging enables the quantitative analysis of tissue recovery and replacement as well as tissue manipulation in the tissue engineering research.clos

Maximum-Area Rectangles in a Simple Polygon

We study the problem of finding maximum-area rectangles contained in a polygon in the plane. There has been a fair amount of work for this problem when the rectangles have to be axis-aligned or when the polygon is convex. We consider this problem in a simple polygon with n vertices, possibly with holes, and with no restriction on the orientation of the rectangles. We present an algorithm that computes a maximum-area rectangle in O(n^3 log n) time using O(kn^2) space, where k is the number of reflex vertices of P. Our algorithm can report all maximum-area rectangles in the same time using O(n^3) space. We also present a simple algorithm that finds a maximum-area rectangle contained in a convex polygon with n vertices in O(n^3) time using O(n) space

Quantitative Screening of Cervical Cancers for Low-Resource Settings: Pilot Study of Smartphone-Based Endoscopic Visual Inspection After Acetic Acid Using Machine Learning Techniques

Background: Approximately 90% of global cervical cancer (CC) is mostly found in low- and middle-income countries. In most cases, CC can be detected early through routine screening programs, including a cytology-based test. However, it is logistically difficult to offer this program in low-resource settings due to limited resources and infrastructure, and few trained experts. A visual inspection following the application of acetic acid (VIA) has been widely promoted and is routinely recommended as a viable form of CC screening in resource-constrained countries. Digital images of the cervix have been acquired during VIA procedure with better quality assurance and visualization, leading to higher diagnostic accuracy and reduction of the variability of detection rate. However, a colposcope is bulky, expensive, electricity-dependent, and needs routine maintenance, and to confirm the grade of abnormality through its images, a specialist must be present. Recently, smartphone-based imaging systems have made a significant impact on the practice of medicine by offering a cost-effective, rapid, and noninvasive method of evaluation. Furthermore, computer-aided analyses, including image processing-based methods and machine learning techniques, have also shown great potential for a high impact on medicinal evaluations

Lamellar keratoplasty using position-guided surgical needle and M-mode optical coherence tomography

Deep anterior lamellar keratoplasty (DALK) is an emerging surgical technique for the restoration of corneal clarity and vision acuity. The big-bubble technique in DALK surgery is the most essential procedure that includes the air injection through a thin syringe needle to separate the dysfunctional region of the cornea. Even though DALK is a well-known transplant method, it is still challenged to manipulate the needle inside the cornea under the surgical microscope, which varies its surgical yield. Here, we introduce the DALK protocol based on the position-guided needle and M-mode optical coherence tomography (OCT). Depth-resolved 26-gage needle was specially designed, fabricated by the stepwise transitional core fiber, and integrated with the swept source OCT system. Since our device is feasible to provide both the position information inside the cornea as well as air injection, it enables the accurate management of bubble formation during DALK. Our results show that real-time feedback of needle end position was intuitionally visualized and fast enough to adjust the location of the needle. Through our research, we realized that position-guided needle combined with M-mode OCT is a very efficient and promising surgical tool, which also to enhance the accuracy and stability of DALK

Snake fang-inspired stamping patch for transdermal delivery of liquid formulations

A flexible microneedle patch that can transdermally deliver liquid-phase therapeutics would enable direct use of existing, approved drugs and vaccines, which are mostly in liquid form, without the need for additional drug solidification, efficacy verification, and subsequent approval. Specialized dissolving or coated microneedle patches that deliver reformulated, solidified therapeutics have made considerable advances; however, microneedles that can deliver liquid drugs and vaccines still remain elusive because of technical limitations. Here, we present a snake fang-inspired microneedle patch that can administer existing liquid formulations to patients in an ultrafast manner (< 15 s). Rear-fanged snakes have an intriguing molar with a groove on the surface, which enables rapid and efficient infusion of venom or saliva into prey. Liquid delivery is based on surface tension and capillary action. The microneedle patch uses multiple open groove architectures that emulate the grooved fangs of rear-fanged snakes: Similar to snake fangs, the microneedles can rapidly and efficiently deliver diverse liquid-phase drugs and vaccines in seconds under capillary action with only gentle thumb pressure, without requiring a complex pumping system. Hydrodynamic simulations show that the snake fang-inspired open groove architectures enable rapid capillary force-driven delivery of liquid formulations with varied surface tensions and viscosities. We demonstrate that administration of ovalbumin and influenza virus with the snake fang-inspired microneedle patch induces robust antibody production and protective immune response in guinea pigs and mice

Metabolic Disturbances Associated with Systemic Lupus Erythematosus

The metabolic disturbances that underlie systemic lupus erythematosus are currently unknown. A metabolomic study was executed, comparing the sera of 20 SLE patients against that of healthy controls, using LC/MS and GC/MS platforms. Validation of key differences was performed using an independent cohort of 38 SLE patients and orthogonal assays. SLE sera showed evidence of profoundly dampened glycolysis, Krebs cycle, fatty acid β oxidation and amino acid metabolism, alluding to reduced energy biogenesis from all sources. Whereas long-chain fatty acids, including the n3 and n6 essential fatty acids, were significantly reduced, medium chain fatty acids and serum free fatty acids were elevated. The SLE metabolome exhibited profound lipid peroxidation, reflective of oxidative damage. Deficiencies were noted in the cellular anti-oxidant, glutathione, and all methyl group donors, including cysteine, methionine, and choline, as well as phosphocholines. The best discriminators of SLE included elevated lipid peroxidation products, MDA, gamma-glutamyl peptides, GGT, leukotriene B4 and 5-HETE. Importantly, similar elevations were not observed in another chronic inflammatory autoimmune disease, rheumatoid arthritis. To sum, comprehensive profiling of the SLE metabolome reveals evidence of heightened oxidative stress, inflammation, reduced energy generation, altered lipid profiles and a pro-thrombotic state. Resetting the SLE metabolome, either by targeting selected molecules or by supplementing the diet with essential fatty acids, vitamins and methyl group donors offers novel opportunities for disease modulation in this disabling systemic autoimmune ailment

NICE 2023 Zero-shot Image Captioning Challenge

In this report, we introduce NICE project\footnote{\url{https://nice.lgresearch.ai/}} and share the results and outcomes of NICE challenge 2023. This project is designed to challenge the computer vision community to develop robust image captioning models that advance the state-of-the-art both in terms of accuracy and fairness. Through the challenge, the image captioning models were tested using a new evaluation dataset that includes a large variety of visual concepts from many domains. There was no specific training data provided for the challenge, and therefore the challenge entries were required to adapt to new types of image descriptions that had not been seen during training. This report includes information on the newly proposed NICE dataset, evaluation methods, challenge results, and technical details of top-ranking entries. We expect that the outcomes of the challenge will contribute to the improvement of AI models on various vision-language tasks.Comment: Tech report, project page https://nice.lgresearch.ai

A review on boiling heat transfer enhancement with nanofluids

There has been increasing interest of late in nanofluid boiling and its use in heat transfer enhancement. This article covers recent advances in the last decade by researchers in both pool boiling and convective boiling applications, with nanofluids as the working fluid. The available data in the literature is reviewed in terms of enhancements, and degradations in the nucleate boiling heat transfer and critical heat flux. Conflicting data have been presented in the literature on the effect that nanofluids have on the boiling heat-transfer coefficient; however, almost all researchers have noted an enhancement in the critical heat flux during nanofluid boiling. Several researchers have observed nanoparticle deposition at the heater surface, which they have related back to the critical heat flux enhancement

Open X-Embodiment:Robotic learning datasets and RT-X models

Large, high-capacity models trained on diverse datasets have shown remarkable successes on efficiently tackling downstream applications. In domains from NLP to Computer Vision, this has led to a consolidation of pretrained models, with general pretrained backbones serving as a starting point for many applications. Can such a consolidation happen in robotics? Conventionally, robotic learning methods train a separate model for every application, every robot, and even every environment. Can we instead train "generalist" X-robot policy that can be adapted efficiently to new robots, tasks, and environments? In this paper, we provide datasets in standardized data formats and models to make it possible to explore this possibility in the context of robotic manipulation, alongside experimental results that provide an example of effective X-robot policies. We assemble a dataset from 22 different robots collected through a collaboration between 21 institutions, demonstrating 527 skills (160266 tasks). We show that a high-capacity model trained on this data, which we call RT-X, exhibits positive transfer and improves the capabilities of multiple robots by leveraging experience from other platforms. The project website is robotics-transformer-x.github.io