Structure-functionality relationship of collagen scaffolds for tissue engineering

Tissue engineering is a promising technology that enables scientists to create artificial organs or replace damaged tissues using animal cells and other components. For successful tissue regeneration, many factors should be taken into account, however, three components are most crucial: cell, scaffold, and soluble factor(s). In order to check the functionality after regeneration of desired tissues, various approaches have been attempted, depending on the physical, biological, and chemical properties of the tissues. Recently, the importance of the extracellular matrix (ECM) microstructure is being considered to be important in this regard. The ECM is closely associated with various functional properties of the tissues including mechanical properties, diffusivity, and hydraulic conductivity or permeability. Besides providing structural support and determining the physical and functional properties, the ECM plays various roles in tissue physiology by regulating cell morphology, growth and intercellular signaling. The ECM can also be reconfigured by cells during tissue remodeling and wound healing. In this thesis, in order to investigate the structure-functionality relationship of engineered tissues (ETs), computational modeling and experimental studies were performed based on the following three topics: (1) the effect of different ECM structures on the tissue transport property, (2) the effect of the different ECM structures on the cell functionality and subsequent tissue mechanical property, and (3) the evaluation of functionality of new vessel networks formed by modulation of ECM structures. ^ The first study developed computational models (i.e., parameter- and image-based models) using experimental data to predict transport properties (i.e.,permeability and diffusivity) of two different microstructural matrices (i.e., monomer and oligomer) for tissue functionality. The developed computational models underestimated the permeability result compared to what was obtained experimentally. The image- and parameter-based models developed in the present study were able to predict values closest to the experiment data, when compared with previously reported models of permeability. For diffusivity, the computational results showed a similar trend and magnitude to the experimental ones. ^ During cryopreservation of tissues, freezing-induced structural deformation of the tissues and cells occurs due to formation of ice within the intracellular and extracellular spaces. Several studies focused on developing optimal combinations of cryoprotective agent (CPA) and freeze/thaw (F/T) protocols for functional tissue and cell preservation. In the second study, a hypothesis was tested that the modulation of the cytoskeletal structure can mitigate the freezing-induced changes of the functionality, therefore, may reduce the amount of CPA necessary to preserve the tissue\u27s functionality during cryopreservation. In order to test the above hypothesis, the engineered tissues (ETs) were exposed to various F/T conditions with or without CPAs, and the freezing-induced cell-fluid-matrix interactions and subsequent functional properties of the ETs were assessed. Our result showed that, the use of only a small concentration of CPA was very successful in completely preserving the elastic modulus and the viscous friction to the state of the unfrozen 3D stressed structure (STR). This result underscores the importance of CPA in preserving the cytoskeleton structure and how that impacts functional properties of the tissue after freeze-thaw cycles. ^ The third study performed the parametric study to estimate endothelium hydraulic conductivity for vessel functionality. Currently, it is known that formation of vasculatures within the tissues is the most difficult aspect of tissue engineering. Moreover, a method to evaluate new vessel functionality has not been well-established to date. Therefore, a new method with the osmotic pressure-driven vessel deformation and the poroelastic theory was developed using new vessel networks formed by vasculogenesis for hydraulic conductivity estimation. Results showed that the hydraulic conductivity was more sensitive to the elastic modulus compared to other parameters. When the elastic modulus with 10 - 100 Pa and Possions\u27s ratio with 0.3 were applied, the hydraulic conductivity was well-matched with the previously reported hydraulic conductivity

Characterizing viscoelastic properties of human melanoma tissue using Prony series

Melanoma is the most invasive and deadly skin cancer, which causes most of the deaths from skin cancer. It has been demonstrated that the mechanical properties of tumor tissue are significantly altered. However, data about characterizing the mechanical properties of in vivo melanoma tissue are extremely scarce. In addition, the viscoelastic or viscous properties of melanoma tissue are rarely reported. In this study, we measured and quantitated the viscoelastic properties of human melanoma tissues based on the stress relaxation test, using the indentation-based mechanical analyzer that we developed previously. The melanoma tissues from eight patients of different ages (57–95), genders (male and female patients), races (White and Asian), and sites (nose, arm, shoulder, and chest) were excised and tested. The results showed that the elastic property (i.e., shear modulus) of melanoma tissue was elevated compared to normal tissue, while the viscous property (i.e., relaxation time) was reduced. Moreover, the tissue thickness had a significant impact on the viscoelastic properties, probably due to the amount of the adipose layer. Our findings provide new insights into the role of the viscous and elastic properties of melanoma cell mechanics, which may be implicated in the disease state and progression

A Pilot Study on the Relationship between Urban Green Spaces and Fine Particulate Matter

This study aims at identifying the relationships among various variables that influence city-wide PM2.5 pollution levels in the six largest cities in Texas. The variables were categorized into three groups for statistical analysis: 1) urban components (city land area, urban population, population density); 2) green space components (coverage, percentage, connectivity, and shape); and 3) meteorological factors (ambient temperature and wind speed). To identify the relationship between meteorological features and daily PM2.5 concentration, we used descriptive statistics for each city and all six cities combined. A bivariate statistical test was used to examine the correlation between urban and green feature components and city-level PM2.5. To avoid a collinearity problem, the combination of variables that have perfect correlation (e.g., city land area and population) were excluded from the statistical model. Lastly, the hierarchical linear modeling (HLM) technique was used to estimate the effects of the meteorological features and urban and green space variables on the daily particle pollution level, which accounts for the clustering of particulate measurements within cities. The results showed that city-wide particulate pollution has significant, positive associations with temperature, city land area, population, population density, and shape complexity, and negative associations with wind speed, amount of green spaces, tree canopy, and connectivity of green spaces. It is notable that there are negative synergies in the cities with higher population density where there was a greater increase in the pollution level. Similarly, the cities with less green spaces exhibited a modest green space mitigation effect, whereas the cities with more green spaces had only a gradual increase in the pollution level even if it increased due to a higher temperature. This study indicates that both the quantity and spatial configuration of green spaces can play an important role in managing fine particulate matter in large cities

Deep learning models for cancer stem cell detection: a brief review

Cancer stem cells (CSCs), also known as tumor-initiating cells (TICs), are a subset of tumor cells that persist within tumors as a distinct population. They drive tumor initiation, relapse, and metastasis through self-renewal and differentiation into multiple cell types, similar to typical stem cell processes. Despite their importance, the morphological features of CSCs have been poorly understood. Recent advances in artificial intelligence (AI) technology have provided automated recognition of biological images of various stem cells, including CSCs, leading to a surge in deep learning research in this field. This mini-review explores the emerging trend of deep learning research in the field of CSCs. It introduces diverse convolutional neural network (CNN)-based deep learning models for stem cell research and discusses the application of deep learning for CSC research. Finally, it provides perspectives and limitations in the field of deep learning-based stem cell research

Safety evaluation on LNG bunkering : to enhance practical establishment of safety zone

This paper is to evaluate the LNG bunkering safety for a 50,000 dead weight tonnage bulk carrier renowned as the world first LNG fuelled bulk carrier. To establish a proper level of the safety zone against the potential risk of gas release from the LNG bunkering systems encompassing from truck to ship, it introduces an enhanced quantitative risk assessment process with two key ideas: firstly, the integration of the population-independent analysis with the population-dependent analysis, and secondly, the combination between the probabilistic analysis and CFD simulation for gas dispersion. Research results reveal that the appropriate levels of the safe zone can be set at 28.8 m in 1E-4 /year criterion that concerns the individual risk of a fatality at the given distance to the risk source of 1 in 10,000 years, whereas at 46.6 m (in 1E-5 /year criterion) and at 213.3 m (in 1E-6 / year criterion) when the area within 5 % and higher gas concentration in air is regarded the critical zone. On the other hand, in case of the critical area considered to be within 2.5 % and higher gas concentration in air, the safety zone will much expand to 34.9 m (in 1E-4 /year criterion), 80.4 m (in 1E-5 /year criterion) and 541.8 m (in 1E-6 /year criterion). These dissimilarities suggest that LNG bunkering ports pay attention to selecting appropriate safety criteria which would considerably change the range of safety zones. The case study also demonstrates the effectiveness of the proposed approach that can remedy the shortcomings/shortfalls of existing technical and regulatory guidance on establishing the zones. It is, therefore, believed that the risk assessment approach proposed in this paper can contribute to determining the appropriate level of safety zones whereas providing practical insight into port authorities and flag states

A framework for determining the life cycle GHG emissions of fossil marine fuels in countries reliant on imported energy through maritime transportation : a case study of South Korea

This research was motivated to address limitations in the current lifecycle assessment frameworks with the absence of proper guidelines for developing default lifecycle values of energies in consideration of supply chain activities and maritime transportation. Given this, it aims to evaluate the level of life cycle GHG emissions of heavy fuel oil, LNG, LPG and methanol as marine fuels produced and supplied in energy import-dependent countries, using South Korea as a case study. The analysis clearly shows that the impact of international shipping on Well-to-Tank (WtT) GHG emissions for energy carriers would be subject to several factors: propulsion system types, the quantify of energy transported, and the routes and distances of voyages. For instance, transportation emissions from LNG carriers for LNG fuel vary significantly depending on the country of import, ranging from 2.26 g CO2 eq./MJ (representing 12.2 % of Well-to-Tank (WtT) emissions for Malaysia) to 5.97 g CO2 eq./MJ (representing 33.3 % of WtT emissions for Qatar). As a preliminary study, an enhancement on the quality of the input/inventory data is imperative for obtaining a reliability of results. Nevertheless, the comparative analysis of different fuels and life stages provides valuable insights for stakeholders to develop effective policies and energy refueling plans for reducing life cycle GHG emissions from marine fuels. These findings could also enhance the current regulatory framework and provide meaningful lifecycle carbon footprints of marine fuels for energy importing countries. The study results also strongly suggest that default values of GHG emission for different countries relying on energy imports via international maritime transport should be further developed in consideration of the impact of regional differences, such as distance, from the importing country for successful arrival of LCA application on marine industry

Associations between Household Latrines and the Prevalence of Diarrhea in Idiofa, Democratic Republic of the Congo: A Cross-Sectional Study.

Despite the importance of sanitation, few studies have assessed the effects of latrines on the health outcomes of children under 5 years of age. We assessed the relations between latrine coverage and the prevalence of diarrhea in children under 4 years of age. In this cross-sectional study, we analyzed the baseline data obtained as part of a longitudinal survey targeting 720 households in Idiofa, Bandundu, Democratic Republic of the Congo. We categorized latrines according to the presence of each major component and investigated whether diarrhea prevalence of children under 4 years of age is associated with latrine availability and improvement. Latrines have health benefits regardless of whether they are improved. Also worth noting is that comparatively well-equipped and more appropriately managed latrines could prevent child diarrhea more effectively than less equipped or inappropriately managed latrines. Households who have a latrine with a superstructure, roof, and no flies (a partly improved latrine) were found to be 52% less likely to report cases of diarrhea than households with unimproved latrines (adjusted odds ratio [OR] = 0.48, confidence interval [CI] = 0.31-0.76), which are all the other latrines not included in the partly improved latrine category. We have observed the profound protective effect of latrines with a superstructure. This study demonstrates that latrines are associated with significant improvements in health even when they do not fully meet the conditions of improved latrines. This study adds value to the limited evidence on the effect of latrines on health parameters by demonstrating that latrines have correlations with health benefits regardless of whether they are improved, as well as by elucidating the most essential components of improved latrines

Effects of improved sanitation on diarrheal reduction for children under five in Idiofa, DR Congo: a cluster randomized trial.

BACKGROUND: The lack of safe water and sanitation contributes to the rampancy of diarrhea in many developing countries. METHODS: This study describes the design of a cluster-randomized trial in Idiofa, the Democratic Republic of the Congo, seeking evidence of the impact of improved sanitation on diarrhea for children under four. Of the 276 quartiers, 18 quartiers were randomly allocated to the intervention or control arm. Seven hundred and-twenty households were sampled and the youngest under-four child in each household was registered for this study. The primary endpoint of the study is diarrheal incidence, prevalence and duration in children under five. DISCUSSION: Material subsidies will be provided only to the households who complete pit digging plus superstructure and roof construction, regardless of their income level. This study employs a Sanitation Calendar so that the mother of each household can record the diarrheal episodes of her under-four child on a daily basis. The diary enables examination of the effect of the sanitation intervention on diarrhea duration and also resolves the limitation of the small number of clusters in the trial. In addition, the project will be monitored through the 'Sanitation Map', on which all households in the study area, including both the control and intervention arms, are registered. To avoid information bias or courtesy bias, photos will be taken of the latrine during the household visit, and a supervisor will determine well-equipped latrine uptake based on the photos. This reduces the possibility of recall bias and under- or over-estimation of diarrhea, which was the main limitation of previous studies. TRIAL REGISTRATION: The study was approved by the Institutional Review Board of the School of Public Health, Kinshasa University (ESP/CE/040/15; April 13, 2015) and registered as an International Standard Randomized Controlled Trial (ISRCTN: 10,419,317) on March 13, 2015

FACES: A Deep-Learning-Based Parametric Model to Improve Rosacea Diagnoses

Rosacea is a chronic inflammatory skin disorder that causes visible blood vessels and redness on the nose, chin, cheeks, and forehead. However, visual assessment, the current standard method used to identify rosacea, is often subjective among clinicians and results in high variation. Recent advances in artificial intelligence have allowed for the effective detection of various skin diseases with high accuracy and consistency. In this study, we develop a new methodology, coined “five accurate CNNs-based evaluation system (FACES)”, to identify and classify rosacea more efficiently. First, 19 CNN-based models that have been widely used for image classification were trained and tested via training and validation data sets. Next, the five best performing models were selected based on accuracy, which served as a weight value for FACES. At the same time, we also applied a majority rule to five selected models to detect rosacea. The results exhibited that the performance of FACES was superior to that of the five individual CNN-based models and the majority rule in terms of accuracy, sensitivity, specificity, and precision. In particular, the accuracy and sensitivity of FACES were the highest, and the specificity and precision were higher than most of the individual models. To improve the performance of our system, future studies must consider patient details, such as age, gender, and race, and perform comparison tests between our model system and clinicians