The Effect of Neonatal Administration of Recombinant Myostatin Propeptide on Skeletal Muscle Growth in Mice.

M.S. Thesis. University of Hawaiʻi at Mānoa 2018

Adsorption Properties of Typical Lung Cancer Breath Gases on Ni-SWCNTs through Density Functional Theory

A lot of useful information is contained in the human breath gases, which makes it an effective way to diagnose diseases by detecting the typical breath gases. This work investigated the adsorption of typical lung cancer breath gases: benzene, styrene, isoprene, and 1-hexene onto the surface of intrinsic and Ni-doped single wall carbon nanotubes through density functional theory. Calculation results show that the typical lung cancer breath gases adsorb on intrinsic single wall carbon nanotubes surface by weak physisorption. Besides, the density of states changes little before and after typical lung cancer breath gases adsorption. Compared with single wall carbon nanotubes adsorption, single Ni atom doping significantly improves its adsorption properties to typical lung cancer breath gases by decreasing adsorption distance and increasing adsorption energy and charge transfer. The density of states presents different degrees of variation during the typical lung cancer breath gases adsorption, resulting in the specific change of conductivity of gas sensing material. Based on the different adsorption properties of Ni-SWCNTs to typical lung cancer breath gases, it provides an effective way to build a portable noninvasive portable device used to evaluate and diagnose lung cancer at early stage in time

Boosting Operational DNN Testing Efficiency through Conditioning

With the increasing adoption of Deep Neural Network (DNN) models as integral parts of software systems, efficient operational testing of DNNs is much in demand to ensure these models' actual performance in field conditions. A challenge is that the testing often needs to produce precise results with a very limited budget for labeling data collected in field. Viewing software testing as a practice of reliability estimation through statistical sampling, we re-interpret the idea behind conventional structural coverages as conditioning for variance reduction. With this insight we propose an efficient DNN testing method based on the conditioning on the representation learned by the DNN model under testing. The representation is defined by the probability distribution of the output of neurons in the last hidden layer of the model. To sample from this high dimensional distribution in which the operational data are sparsely distributed, we design an algorithm leveraging cross entropy minimization. Experiments with various DNN models and datasets were conducted to evaluate the general efficiency of the approach. The results show that, compared with simple random sampling, this approach requires only about a half of labeled inputs to achieve the same level of precision.Comment: Published in the Proceedings of the 27th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE 2019

Rainbow Trapping with Long Oscillation Lifetimes in Gradient Magnetoinductive Metasurfaces

We report a gradient metasurface design at microwave bands as an elegant approach to realize the goal of “rainbow trapping” for the storage of waves involving wave localization and absorption phenomena. A longitudinally placed coplanar waveguide is loaded with gradient metasurfaces on both sides, where split-ring resonators (SRRs) are the basic cell. The same SRRs are arranged along the transverse direction to establish magnetoinductive channels. Waves of different frequencies are coupled to corresponding SRRs at different positions in metasurfaces. Resonant trapping with a long oscillation life time enhances the absorption caused by inherent losses of the materials, thereby suppressing reflections. Both simulations and measurements verify the existence of “rainbow trapping.” The proposed strategy enhances the interaction between waves and matter, opening an avenue for further component designs, including absorptive filters, multiplexers, and buffers

DPAC: An infrastructure for dynamic program analysis of concurrency Java programs

ABSTRACT Concurrency programs are hard to test or debug due to their nondeterministic nature. Existing dynamic program analysis approaches tried to address this by carefully examine a recorded execution trace. However, developing such analysis tools is complicated, requiring to take care of many tedious implementation details, and comparing and evaluating different analysis approaches are also subject to various biases, due to lack of a common base platform. This motivates us to design DPAC, an infrastructure that support in building dynamic program analysis tools for concurrency Java programs. DPAC takes events and their various processing mechanisms as its underlying model to facilitate monitoring and manipulation of program executions as required by dynamic program analysis. Various analysis tools can be implemented by customizing their required event types and processing mechanisms. We show two concrete case studies how our DPAC helps building existing dynamic program analysis approaches, as well as tuning subtle implementation details for supporting customized function implementation and code transformation

Automating Object Transformations for Dynamic Software Updating via Online Execution Synthesis

Dynamic software updating (DSU) is a technique to upgrade a running software system on the fly without stopping the system. During updating, the runtime state of the modified components of the system needs to be properly transformed into a new state, so that the modified components can still correctly interact with the rest of the system. However, the transformation is non-trivial to realize due to the gap between the low-level implementations of two versions of a program. This paper presents AOTES, a novel approach to automating object transformations for dynamic updating of Java programs. AOTES bridges the gap by abstracting the old state of an object to a history of method invocations, and re-invoking the new version of all methods in the history to get the desired new state. AOTES requires no instrumentation to record any data and thus has no overhead during normal execution. We propose and implement a novel technique that can synthesize an equivalent history of method invocations based on the current object state only. We evaluated AOTES on software updates taken from Apache Commons Collections, Tomcat, FTP Server and SSHD Server. Experimental results show that AOTES successfully handled 51 of 61 object transformations of 21 updated classes, while two state-of-the-art approaches only handled 11 and 6 of 61, respectively

The Fas/Fap-1/Cav-1 complex regulates IL-1RA secretion in mesenchymal stem cells to accelerate wound healing

Mesenchymal stem cells (MSCs) are capable of secreting exosomes, extracellular vesicles, and cytokines to regulate cell and tissue homeostasis. However, it is unknown whether MSCs use a specific exocytotic fusion mechanism to secrete exosomes and cytokines. We show that Fas binds with Fas-Associated phosphatase-1 (Fap-1) and caveolin-1 (Cav-1) to activate a common soluble N-ethylmaleimide-sensitive factor (NSF) attachment protein receptor (SNARE)-mediated membrane fusion mechanism to release small extracellular vesicles (sEVs) in MSCs. Moreover, we reveal that MSCs produce and secrete interleukin-1 receptor antagonist (IL-1RA) associated with sEVs to maintain rapid wound healing in the gingiva via the Fas/Fap-1/Cav-1 cascade. Tumor necrosis factor-? (TNF-?) serves as an activator to up-regulate Fas and Fap-1 expression via the nuclear factor ?B pathway to promote IL-1RA release. This study identifies a previously unknown Fas/Fap-1/Cav-1 axis that regulates SNARE-mediated sEV and IL-1RA secretion in stem cells, which contributes to accelerated wound healing. © 2018 The Authors, Some Rights Reserved

Drug-eluting stents for coronary artery disease in the perspective of bibliometric analysis

Drug-eluting stents (DES) play a crucial role in treating coronary artery disease (CAD) by preventing restenosis. These stents are coated with drug carriers that release antiproliferative drugs within the vessel. Over the past two decades, DES have been employed in clinical practice using various materials, polymers, and drug types. Despite optimizations in their design and materials to enhance biocompatibility and antithrombotic properties, evaluating their long-term efficacy and safety necessitates improved clinical follow-up and monitoring. To delineate future research directions, this study employs a bibliometric analysis approach. We comprehensively surveyed two decades' worth of literature on DES for CAD using the Web of Science Core Collection (WOSCC). Out of 5,778 articles, we meticulously screened them based on predefined inclusion and exclusion criteria. Subsequently, we conducted an in-depth analysis encompassing annual publication trends, authorship affiliations, journal affiliations, keywords, and more. Employing tools such as Excel 2021, CiteSpace 6.2R3, VOSviewer 1.6.19, and Pajek 5.17, we harnessed bibliometric methods to derive insights from this corpus. Analysis of annual publication data indicates a recent stabilisation or even a downward trend in research output in this area. The United States emerged as the leading contributor, with Columbia University and CRF at the forefront in both publication output and citation impact. The most cited document pertained to standardized definitions for clinical endpoints in coronary stent trials. Our author analysis identifies Patrick W. Serruys as the most prolific contributor, underscoring a dynamic exchange of knowledge within the field.Moreover, the dual chart overlay illustrates a close interrelation between journals in the “Medicine,” “Medical,” and “Clinical” domains and those in “Health,” “Nursing,” and “Medicine.” Frequently recurring keywords in this research landscape include DES coronary artery disease, percutaneous coronary intervention, implantation, and restenosis. This study presents a comprehensive panorama encompassing countries, research institutions, journals, keyword distributions, and contributions within the realm of DES therapy for CAD. By highlighting keywords exhibiting recent surges in frequency, we elucidate current research hotspots and frontiers, thereby furnishing novel insights to guide future researchers in this evolving field

Characterization of ultra-deeply buried middle Triassic Leikoupo marine carbonate petroleum system (!) in the Western Sichuan depression, China

Ultra-deeply buried (>5000 m) marine carbonate reservoirs have gradually become important exploration targets. This research focuses on providing an understanding of the basic elements of the ultra-deeply buried Middle Triassic Leikoupo marine carbonate petroleum system within the Western Sichuan Depression, China. Comprehensive analyses of organic geochemistry, natural gas, and C–H–He–Ne–Ar isotope compositions suggest that the reservoir is charged with compound gases from four source rock units including the Permian Longtan, Middle Triassic Leikoupo, Late Triassic Maantang and Xiaotangzi formations. Approximately a 50-m thick outcrop and 100-m length of drilling cores were examined in detail, and 108 samples were collected from six different exploration wells in order to conduct petrographic and petrophysical analyses. Thin-section and scanning electron microscope (SEM) observations, helium porosity and permeability measurements, mercury injection capillary pressure (MICP) analysis, and wire-line logging (5,500–6,900 m) indicate that the reservoir lithologies include argillaceous algal limestones, dolograinstones, crystalline dolostones, and microbially-derived stromatolitic and thrombolitic dolostones. Reservoir properties exhibit extreme heterogeneity due to different paleogeographic environmental controls and mutual interactions between constructive (e.g., epigenetic paleo-karstification, burial dissolution, structural movement, pressure-solution and dolomitization) and destructive (e.g., physical/chemical compaction, cementation, infilling, recrystallization, and replacement) diagenetic processes. An unconformity-related epigenetic karstification zone was identified in the uppermost fourth member of the Leikoupo Formation, which has developed secondary solution-enhanced pores, vugs, and holes that resulted in higher porosity (1.8–14.2%) and permeability (0.2–7.7 mD). The homogeneity and tightness of the reservoir increases with depth below the unconformity, and it is characterized by primary intergranular and intracrystalline pores, solution pores, fractures, stylolites, and micropores with a lower helium porosity (0.6–4.1%) and permeability (0.003–125.2 mD). Regional seals consist of the Late Triassic Xujiahe Formation, comprised of ~300 m of mudstones that are overlain by ~5,000-m thick of Jurassic to Quaternary continental argillaceous overburden rocks. Effective traps are dominated by a combination of structural-stratigraphic types. Paleo- reservoir crude oil cracking, wet-gases, and dry-gases from three successive hydrocarbon generation processes supplied the sufficient hydrocarbon resources. The homogenization temperatures of the hydrocarbon-associated aqueous fluid inclusions range from 98–130 °C and 130–171 °C, which suggests hydrocarbon charging occurred between 220–170 Ma and 130–90 Ma, respectively. One-dimensional basin evolution models combined with structural geologic and seismic profiles across wells PZ1-XQS1-CK1-XCS1-TS1 show that hydrocarbon migration and entrapment mainly occurred via the unconformity and interconnected fault-fracture networks with migration and charging driven by formation overpressure, abnormal fluid flow pressure, and buoyancy forces during the Indosinian and Yanshanian orogenies, with experiencing additional transformation occurring during the Himalayan orogeny. The predicted estimated reserves reached ~300 × 109 m3. The results provide excellent scientific implications for similar sedimentary basin studies, it is believed that abundant analogous deeply buried marine carbonate hydrocarbon resources yet to be discovered in China and elsewhere worldwide in the near future