Search results for: 177Lu labeled somatostatin analogues

Authors: Priyanka Sharma, Niti Puri

Abstract:

Anemia develops when blood lacks enough healthy erythrocytes. Past studies indicated that anemia, inflammatory process, and oxidative stress are interconnected. Erythrocytes are continuously exposed to reactive oxygen species (ROS) during circulation, due to normal aerobic cellular metabolism and also pathology of inflammatory diseases. Systemic mastocytosis and genetic depletion of mast cells have been shown to affect anaemia. In the present study, we attempted to reveal whether mast cells have a direct role in clearance or erythrophagocytosis of normal or oxidatively damaged erythrocytes. Murine erythrocytes were treated with tert-butyl hydroperoxidase (t-BHP), an agent that induces oxidative damage and mimics in vivo oxidative stress. Normal and oxidatively damaged erythrocytes were labeled with carboxyfluorescein succinimidyl ester (CFSE) to track erythrophagocytosis. We show, for the first time, direct erythrophagocytosis of oxidatively damaged erythrocytes in vitro by RBL-2H3 mast cells as well as in vivo by murine peritoneal mast cells. Also, activated mast cells, as may be present in inflammatory conditions, showed a significant increase in the uptake of oxidatively damaged erythrocytes than resting mast cells. This suggests the involvement of mast cells in erythrocyte clearance during oxidative stress or inflammatory disorders. Partial inhibition of phagocytosis by various inhibitors indicated that this process may be controlled by several pathways. Hence, our study provides important evidence for involvement of mast cells in severe anemia due to inflammation and oxidative stress and might be helpful to circumvent the adverse anemic disorders.

Keywords: mast cells, anemia, erythrophagocytosis, oxidatively damaged erythrocytes

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Authors: Danila Merino, Leandro N. Ludueña, Vera A. Alvarez

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Clays are commonly used to reinforce polymeric materials. In order to modify them, long-chain quaternary-alkylammonium salts have been widely employed. However, the application of these clays in biological fields is limited by the toxicity and poor biocompatibility presented by these modifiers. Meanwhile, soy lecithin, acts as a natural biosurfactant and environment-friendly biomodifier. In this report, we analyse the effect of content of soy lecithin-modified bentonite on the properties of polycaprolactone (PCL) nanocomposites. Commercial grade PCL (CAPA FB 100) was supplied by Perstorp, with Mw = 100000 g/mol. Minarmco S.A. and Melar S.A supplied bentonite and soy lecithin, respectively. Clays with 18, 30 and 45 wt% of organic content were prepared by exchanging 4 g of Na-Bent with 1, 2 and 4 g of soy lecithin aqueous and acid solution (pH=1, with HCl) at 75ºC for 2 h. Then, they were washed and lyophilized for 72 h. Samples were labeled A, B and C. Nanocomposites with 1 and 2 wt.% of each clay were prepared by melt-intercalation followed by compression-moulding. An intensive Brabender type mixer with two counter-rotating roller rotors was used. Mixing temperature was 100 ºC; speed of rotation was 100 rpm. and mixing time was 10 min. Compression moulding was carried out in a hydraulic press under 75 Kg/mm2 for 10 minutes at 100 ºC. The thickness of the samples was about 1 mm. Thermal and mechanical properties were analysed. PCL nanocomposites with 1 and 2% of B presented the best mechanical properties. It was observed that an excessive organic content produced an increment on the rigidity of PCL, but caused a detrimental effect on the tensile strength and elongation at break of the nanocomposites. Thermogravimetrical analyses suggest that all reinforced samples have higher resistance to degradation than neat PCL.

Keywords: chemical modification, clay, nanocomposite, characterization

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Authors: Parul Suraia, Harshit Sosan Lakra

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Indigenous communities represent some of the most marginalized populations globally, with India labeled as tribals, experiencing particularly pronounced marginalization and a concerning decline in their numbers. These communities often inhabit geographically challenging regions characterized by low population densities, posing significant challenges to providing essential infrastructure services. Jharkhand, a Schedule 5 state, is infamous for its low-level health status due to disparities in access to health care. The primary objective of this study is to investigate the spatial inequalities in healthcare accessibility among tribal populations within the state and pinpoint critical areas requiring immediate attention. Health indicators were selected based on the tribal perspective and association of Sustainable Goal 3 (Good Health and Wellbeing) with other SDGs. Focused group discussions in which tribal people and tribal experts were done in order to finalize the indicators. Employing Principal Component Analysis, two essential indices were constructed: the Tribal Health Index (THI) and the Tribal Health Intervention Index (THII). Index values were calculated based on the district-wise secondary data for Jharkhand. The bivariate spatial association technique, Moran’s I was used to assess the spatial pattern of the variables to determine if there is any clustering (positive spatial autocorrelation) or dispersion (negative spatial autocorrelation) of values across Jharkhand. The results helped in facilitating targeting policy interventions in deprived areas of Jharkhand.

Keywords: tribal health, health spatial disparities, health status, Jharkhand

Procedia PDF Downloads 90

Authors: Itay Harlap

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Over the past decade, LGBT figures have become increasingly visible on Israeli television in its various channels and genres. In recent years, however, the representation of gays on Israeli television has undergone an interesting shift, whereby many television texts feature gay people as fathers. These texts, mostly news items and documentaries, usually present gay parenthood as a positive phenomenon. The question in paper is whether LGBT parenting (in reality and as representation) fated to be part of the homonormativity that characterizes the LGBT community in Israel, or can it be an alternative to the hegemonic discourse? This paper embraces a dialectical position and explores the tension between mainstream and radical, or homonormativity and queer politics in the specific Israeli Jewish context through a textual and discursive reading of a selection of television programs that revolve principally around gay parenting in Israel. The first part of this lecture addresses the cultural and social context that generated these representations, dealing with three key Israeli areas: The fertility cult, the evolution of the LGBT community, and the evolution of local television. The second part offers a queer reading of these ‘positive’ representations (mainly in special reports on the news and programs labeled as ‘documentaries’ by broadcasters) and highlight the possible price of the ‘bear hug’ given by Israeli media to gay parents. The last part focuses on a single case study, the TV serial drama Ima Veabaz, and suggests that this drama exposes the performative aspect of parenting and the connection between ethnicity and fertility, and offers an alternative to normative displays of gay parenting.

Keywords: fatherhood, heteronormativity, Israel, queer theory, television

Procedia PDF Downloads 361

Authors: Jian Li

Abstract:

The uncertainty quantification and inversion problems of subsurface oil-water phase flow usually require extensive repeated forward calculations for new runs with changed conditions. To reduce the computational time, various forms of surrogate models have been built. Related research shows that deep learning has emerged as an effective surrogate model, while most surrogate models with deep learning are purely data-driven, which always leads to poor robustness and abnormal results. To guarantee the model more consistent with the physical laws, a coupled theory-guided convolutional neural network (TgCNN) based surrogate model is built to facilitate computation efficiency under the premise of satisfactory accuracy. The model is a convolutional neural network based on multi-well reservoir simulation. The core notion of this proposed method is to bridge two separate blocks on top of an overall network. They underlie the TgCNN model in a coupled form, which reflects the coupling nature of pressure and water saturation in the two-phase flow equation. The model is driven by not only labeled data but also scientific theories, including governing equations, stochastic parameterization, boundary, and initial conditions, well conditions, and expert knowledge. The results show that the TgCNN-based surrogate model exhibits satisfactory accuracy and efficiency in subsurface oil-water phase flow under multi-well conditions.

Keywords: coupled theory-guided convolutional neural network, multi-well conditions, surrogate model, subsurface oil-water phase

Procedia PDF Downloads 81

Authors: Masood Varshosaz, Kamyar Hasanpour

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In recent years, we have seen growing interest in recognizing humans in drone images for post-disaster search and rescue operations. Deep learning algorithms have shown great promise in this area, but they often require large amounts of labeled data to train the models. To keep the data acquisition cost low, augmentation techniques can be used to create additional data from existing images. There are many techniques of such that can help generate variations of an original image to improve the performance of deep learning algorithms. While data augmentation is potentially assumed to improve the accuracy and robustness of the models, it is important to ensure that the performance gains are not outweighed by the additional computational cost or complexity of implementing the techniques. To this end, it is important to evaluate the impact of data augmentation on the performance of the deep learning models. In this paper, we evaluated the most currently available 2D data augmentation techniques on a standard convolutional network which was trained for recognizing humans in drone images. The techniques include rotation, scaling, random cropping, flipping, shifting, and their combination. The results showed that the augmented models perform 1-3% better compared to a base network. However, as the augmented images only contain the human parts already visible in the original images, a new data augmentation approach is needed to include the invisible parts of the human body. Thus, we suggest a new method that employs simulated 3D human models to generate new data for training the network.

Keywords: human recognition, deep learning, drones, disaster mitigation

Procedia PDF Downloads 88

Authors: Simona Grasso, Gabrielle Smith, Sophie Bowers, Oluseyi Moses Ajayi, Mark Swainson

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Hybrid meat analogues are meat products whereby a proportion of meat has been partially replaced by more sustainable protein sources. These products could bridge the gap between meat and meat-free products, providing convenience, and allowing consumers to continue using meat products as they conventionally would, while lowering their overall meat intake. The study aimed to investigate the effect of introducing texturized soy protein (TSP) at different levels (15% and 30%) with and without nutritional yeast as flavour enhancer on the sensory and instrumental quality of beef meatballs, compared to a soy and yeast-free control. Proximate analysis, yield, colour, instrumental texture, and sensory quality were investigated. The addition of soy and yeast did not have significant effects on the overall protein content, but the total fat and moisture content went down with increasing soy substitution. Samples with 30% TSP had significantly higher yield than the other recipes. In terms of colour, a* redness values tended to go down and b* yellowness values tended to go up with increasing soy addition. The addition of increasing levels of soy and yeast modified the structure of meatballs resulting in a progressive decrease in hardness and chewiness compared to control. Sixty participants assessed the samples using Check-all-that-apply (CATA) questions and hedonic scales. The texture of all TSP-containing samples received significantly higher acceptability scores than control, while 15% TSP with yeast received significantly higher flavour and overall acceptability scores than control. Control samples were significantly more often associated than the other recipes to the term 'hard' and the least associated to 'soft' and 'crumbly and easy to cut'. All recipes were similarly associated to the terms 'weak meaty', 'strong meaty', 'characteristic' and 'unusual'. Correspondence analysis separated the meatballs in three distinct groups: 1) control; 2) 30%TSP with yeast; and 3) 15%TSP, 15%TSP with yeast and 30%TSP located together on the sensory map, showing similarity. Adding 15-30% TSP with or without yeast inclusion could be beneficial for the development of future meat hybrids with acceptable sensory quality. These results can provide encouragement for the use of the hybrid concept by the meat industry to promote the partial substitution of meat in flexitarians’ diets.

Keywords: CATA, hybrid meat products, texturised soy protein, yeast

Procedia PDF Downloads 161

Authors: Mehrnaz Aminitabar, Moghan Amirhosseinian, Morteza Elsa

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Bioactive glasses (BGs) are a group of surface-reactive biomaterials used in clinical applications as implants or filler materials in the human body to repair and replace diseased or damaged bone. Sol-gel technique was employed to prepare a SiO₂-CaO-P₂O₅ glass with nominal composition of 58S BG with the addition of Sr and Li modifiers which imparts special properties to the BG. The effect of simultaneous addition of Sr and Li on bioactivity and biocompatibility, proliferation, alkaline phosphatase (ALP) activity of osteoblast cell line MC3T3-E1 and antibacterial property against methicillin-resistant Staphylococcus aureus (MRSA) bacteria were examined. BGs were characterized by X-ray diffraction, Fourier transform infrared spectroscopy, scanning electron microscopy before and after soaking the samples in the simulated body fluid (SBF) for different time intervals to characterize the formation of hydroxyapatite (HA) formed on the surface of BGs. Structural characterization indicated that the simultaneous presence of 5% Sr and 5% Li in 58S-BG composition not only did not retard HA formation because of opposite effect of Sr and Li of the dissolution of BG in the SBF but also, stimulated the differentiation and proliferation of MC3T3-E1s. Moreover, the presence of Sr and Li on dissolution of the ions resulted in an increase in the mean number of DAPI-labeled nuclei which was in good agreement with live/dead assay. The result of antibacterial tests revealed that Sr and Li-substituted 58S BG exhibited a potential antibacterial effect against MRSA bacteria. Because of optimal proliferation and ALP activity of MC3T3-E1cells, proper bioactivity and high antibacterial potential against MRSA, BG-5/5 is suggested as a multifunctional candidate for bone tissue engineering.

Keywords: antibacterial activity, bioactive glass, sol-gel, strontium

Procedia PDF Downloads 114

Authors: Zonglin Yang, Tatsuya Akiyama, Kerry S. Williamson, Michael J. Franklin, Thiruvarangan Ramaraj

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Pseudomonas aeruginosa is an opportunistic pathogen that forms surface-associated microbial communities (biofilms) on artificial implant devices and on human tissue. Biofilm infections are difficult to treat with antibiotics, in part, because the bacteria in biofilms are physiologically heterogeneous. One measure of biological heterogeneity in a population of cells is to quantify the cellular concentrations of ribosomes, which can be probed with fluorescently labeled nucleic acids. The fluorescent signal intensity following fluorescence in situ hybridization (FISH) analysis correlates to the cellular level of ribosomes. The goals here are to provide computationally and statistically robust approaches to automatically quantify cellular heterogeneity in biofilms from a large library of epifluorescent microscopy FISH images. In this work, the initial steps were developed toward these goals by developing an automated biofilm detection approach for use with FISH images. The approach allows rapid identification of biofilm regions from FISH images that are counterstained with fluorescent dyes. This methodology provides advances over other computational methods, allowing subtraction of spurious signals and non-biological fluorescent substrata. This method will be a robust and user-friendly approach which will enable users to semi-automatically detect biofilm boundaries and extract intensity values from fluorescent images for quantitative analysis of biofilm heterogeneity.

Keywords: image informatics, Pseudomonas aeruginosa, biofilm, FISH, computer vision, data visualization

Procedia PDF Downloads 129

Authors: Yasser A. Ahmed, Juleen M Dickson, Evan S. Krystofiak, Julie A. Oliver

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Cancer cells urgently need folate to support their rapid division. Folate receptors (FR) are over-expressed on a wide range of tumor cells, including breast cancer cells. FR are distributed over the entire surface of cancer cells, but are polarized to the apical surface of normal cells. Targeting of cancer cells using specific surface molecules such as folate receptors may be one of the strategies used to kill cancer cells without hurting the neighing normal cells. The aim of the current study was to try a method of SEM detecting FR in a murine breast cancer cell model (4T1 cells) using secondary antibody conjugated to gold or gold-coated magnetite nanoparticles. 4T1 cells were suspended in RPMI medium witth FR antibody and incubated with secondary antibody for fluorescence microscopy. The cells were cultured on 30mm Thermanox coverslips for 18 hours, labeled with FR antibody then incubated with secondary antibody conjugated to gold or gold-coated magnetite nanoparticles and processed to scanning electron microscopy (SEM) analysis. The fluorescence microscopy study showed strong punctate FR expression on 4T1 cell membrane. With SEM, the labeling with gold or gold-coated magnetite conjugates showed a similar pattern. Specific labeling occurred in nanoparticle clusters, which are clearly visualized in backscattered electron images. The 4T1 tumor cell model may be useful for the development of FR-targeted tumor therapy using gold-coated magnetite nano-particles.

Keywords: cancer cell, nanoparticles, cell culture, SEM

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Authors: Somaye Sabetnia

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This paper is accomplished to probe Susanna Kaysen’s memoir Girl, Interrupted in the light of Michel Foucault’s theory of madness comprehensively set forth in his History of Madness (1961). It is an endeavor to analysis this novel based on Foucault’s idea of madness. In his archeological study of madness, Foucault introduces a way to perceive madness and its association with dominant discourses. He argues that the concept of madness is constructed within the social context, and different institutions affect its definition. Furthermore, he takes into consideration how each era treats madness, and affirms that in modern times, people considered mad are exiled out of cities, confined in madhouses, and later in clinics where they are treated with drugs. Set after World War II, the novel under observation highlights women’s conditions in which they were becoming a housewife or following their own desires; in fact, choosing the second one results in labeling mad. The protagonist of novel is labeled 'mad,' and is hence impelled to go to asylums where so-called patients are under the vigilant surveillance of the authorities to go through the process of 'normalization.' To discern how she is considered 'mad,' this article probes the dominant discourse of the time when the stories take place to provide a better understanding of madness under the impact of social, cultural, and political conditions. It examines how a so-called mad considered 'Other' and treated after being confined by the disciplinary system of the asylum in a panoptic world. In addition to, it describes the aim of treatment is to punish and control a patient not to cure. This article aims to indicate that Susanna Kaysen tries to picture what is defined as women’s madness is the result of the patriarchal society of the post-war America as well as the mental illness has nothing to do with blood; it is rather the result of the social inequality of the age.

Keywords: clinical treatment, disciplining and punishment, dominant discourse, normalization, other, panoptic world, reason vs. unreason

Procedia PDF Downloads 318

Authors: Miriam Palomo-Nieto, Adrian Agricola, Rudolf Psotta, Reza Abdollahipour, Ludvik Valtr

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The importance of vision and the visual control of movement have been labeled in the literature related to motor control and many studies have demonstrated that children with low motor competence may rely more heavily on vision to perform movements than their typically developing peers. The aim of the study was to highlight the effects of different visual conditions on motor performance during walking in children with different levels of motor coordination. Participants (n = 32, mean age = 8.5 years sd. ± 0.5) were divided into two groups: typical development (TD) and low motor coordination (LMC) based on the scores of the Movement Assessment Battery for Children (MABC-2). They were asked to walk along a 10 meters walkway where the Optojump-Next instrument was installed in a portable laboratory (15 x 3 m), which allows that all participants had the same visual information. They walked in self-selected speed under four visual conditions: full vision (FV), limited vision 100 ms (LV-100), limited vision 150 ms (LV-150) and non-vision (NV). For visual occlusion participants were equipped with Plato Goggles that shut for 100 and 150 ms, respectively, within each 2 sec. Data were analyzed in a two-way mixed-effect ANOVA including 2 (TD vs. LMC) x 4 (FV, LV-100, LV-150 & NV) with repeated-measures on the last factor (p ≤.05). Results indicated that TD children walked faster and with longer normalized steps length and strides than LMC children. For TD children the percentage of the single support and swing time were higher than for low motor competence children. However, the percentage of load response and pre swing was higher in the low motor competence children rather than the TD children. These findings indicated that through walking we could be able to identify different levels of motor coordination in children. Likewise, LMC children showed shorter percentages in those parameters regarding only one leg support, supporting the idea of balance problems.

Keywords: visual information, motor performance, walking pattern, optojump

Procedia PDF Downloads 571

Authors: Jiangxia Han, Liang Xue, Keda Chen

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Despite the significant progress over the last decades in reservoir simulation using numerical discretization, meshing is complex. Moreover, the high degree of freedom of the space-time flow field makes the solution process very time-consuming. Therefore, we present Physics-Informed Convolutional Neural Networks(PICNN) as a hybrid scientific theory and data method for reservoir modeling. Besides labeled data, the model is driven by the scientific theories of the underlying problem, such as governing equations, boundary conditions, and initial conditions. PICNN integrates governing equations and boundary conditions into the network architecture in the form of a customized convolution kernel. The loss function is composed of data matching, initial conditions, and other measurable prior knowledge. By customizing the convolution kernel and minimizing the loss function, the neural network parameters not only fit the data but also honor the governing equation. The PICNN provides a methodology to model and history-match flow and transport problems in porous media. Numerical results demonstrate that the proposed PICNN can provide an accurate physical solution from a limited dataset. We show how this method can be applied in the context of a forward simulation for continuous problems. Furthermore, several complex scenarios are tested, including the existence of data noise, different work schedules, and different good patterns.

Keywords: convolutional neural networks, deep learning, flow and transport in porous media, physics-informed neural networks, reservoir simulation

Procedia PDF Downloads 137

Authors: Hanan Yousef, Nisreen Naji Al-Khawaldeh

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The present study investigates the use of the expression of refusal by native speakers of Jordanian Arabic (NSsJA) in different social situations (i.e. invitations, suggestions, and offers). It also investigates the influence of gender on the refusal realization patterns within the Jordanian culture to provide a better insight into the relation between situations, strategies and gender in the Jordanian culture. To that end, a group of 70 participants, including 35 male and 35 female students from different departments at the Hashemite University (HU) participated in this study using mixed methods (i.e. Discourse Completion Test (DCT), interviews and naturally occurring data). Data were analyzed in light of a developed coding scheme. The results showed that NSsJA preferred indirect strategies which mitigate the interaction such as "excuse, reason and, explanation" strategy more than other strategies which aggravate the interaction such as "face-threatening" strategy. Moreover, the analysis of this study has revealed a considerable impact of gender on the use of linguistic forms expressing refusal among NSsJA. Significant differences in the results of the Chi-square test relating the effect of participants' gender indicate that both males and females were conscious of the gender of their interlocutors. The findings provide worthwhile insights into the relation amongst types of communicative acts and the rapport between people in social interaction. They assert that refusal should not be labeled as face threatening act since it does not always pose a threat in some cases especially where refusal is expressed among friends, relatives and family members. They highlight some distinctive culture-specific features of the communicative acts of refusal.

Keywords: gender, Jordanian Arabic, politeness, refusals, speech act

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Authors: M. E. Hammond, R. Pokorny

Abstract:

Not much research has gone into the dynamics of natural regeneration of trees species in tropical forest regions. This study seeks to investigate the impact of gap sizes and light distribution in forest floors on the regeneration of Celtis mildbraedii (CEM), Nesogordonia papaverine (NES) and Terminalia superba (TES). These are selected economically important tree species with different shade tolerance attributes. The spatial distribution patterns and the potential regeneration competition index (RCI) among species using height to diameter ratio (HDR) have been assessed. Gap sizes ranging between 287 – 971 m² were selected at the Bia Tano forest reserve, a tropical moist semi-deciduous forest in Ghana. Four (4) transects in the cardinal directions were constructed from the center of each gap. Along each transect, ten 1 m² sampling zones at 2 m spacing were established. Then, three gap microsites (labeled ecozones I, II, III) were delineated within these sampling zones based on the varying temporal light distribution on the forest floor. Data on height (H), root collar diameter (RCD) and regeneration census were gathered from each of the ten sampling zones. CEM and NES seedlings (≤ 50 cm) and saplings (≥ 51 cm) were present in all ecozones of the large gaps. Seedlings of TES were observed in all ecozones of large and small gaps. Regression analysis showed a significant negative linear relationship between independent RCD and H growth variables on dependent HDR index in ecozones II and III of both large and small gaps. There was a correlation between RCD and H in both large and small gaps. A strong regeneration competition was observed among species in ecozone II in large (df 2, F=3.6, p=0.035) and small (df 2, F=17.9, p=0.000) gaps. These results contribute to the understanding of the natural regeneration of different species with regards to light regimes in forest floors.

Keywords: Celtis mildbraedii, ecozones, gaps, Nesogordonia papaverifera, regeneration, Terminalia superba

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Authors: Bahador Bardshiri, Omid Moradi, Amir Komeilian, Nima Panahifar

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Formation of a conjunctival membrane over the corneal surface is a condition unique to rabbits that has been labeled aberrant corneal occlusion or pseudopterygium. In the summer of 2013, a five years old male Standard Chinchilla rabbit were presented to Karaj Central Veterinary hospital and the owner complained that his rabbit shows degrees of blindness and there were opacities on both eyes of the presented rabbit. Ophthalmic examination of the affected eyes revealed a conjunctival fold stretching over the cornea of both eyes. The fold originated from limbus and it was vascularized and centrally thickened. There were no attachments to the corneal epithelium and the fold could be easily lifted. Surgery was performed under general anesthesia. The conjunctival fold was incised centrifugally up to its attachment at the limbus and the lid margin using small scissors. The central rim of the segment was then replaced to its normal position in the fornix and fixed with mattress sutures (7/0) passing through outside skin. After the surgery, eye drops containing dexamethasone, gentamicin and polymixin were applied twice daily up to 3 weeks. Within the observation period (8 months) no recurrence was noted. "Pseudo" in the term pseudopterygium refers to the fact that the conjunctival membrane is not adhering to the underlying cornea, but growing over it. In rare cases, the membrane may be loosely attached to the cornea, but can be easily separated without causing damage. It can cover only a small part of the cornea with an annular peripheral opacification of the cornea, or cover it almost fully, leading to blindness. Ethiopathogenesis remains unclear and recurrence of the problem is very likely. The surgical technique that used here decreases probability of recurrence of conjunctival fold.

Keywords: rabbit, cornea, aberrant corneal occlusion, pseudopterygium

Procedia PDF Downloads 338

Authors: Melanie Ostermann, Eivind Birkeland, Ying Xue, Alexander Sauter, Mihaela R. Cimpan

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Background: New reliable and robust techniques to assess biological effects of nanomaterials (NMs) in vitro are needed to speed up safety analysis and to identify key physicochemical parameters of NMs, which are responsible for their acute cytotoxicity. The central aim of this study was to validate and evaluate the applicability and reliability of an impedance-based flow cytometry (IFC) technique for the high-throughput screening of NMs. Methods: Eight inorganic NMs from the European Commission Joint Research Centre Repository were used: NM-302 and NM-300k (Ag: 200 nm rods and 16.7 nm spheres, respectively), NM-200 and NM- 203 (SiO₂: 18.3 nm and 24.7 nm amorphous, respectively), NM-100 and NM-101 (TiO₂: 100 nm and 6 nm anatase, respectively), and NM-110 and NM-111 (ZnO: 147 nm and 141 nm, respectively). The aim was to assess the biological effects of these materials on human monoblastoid (U937) cells. Dispersions of NMs were prepared as described in the NANOGENOTOX dispersion protocol and cells were exposed to NMs at relevant concentrations (2, 10, 20, 50, and 100 µg/mL) for 24 hrs. The change in electrical impedance was measured at 0.5, 2, 6, and 12 MHz using the IFC AmphaZ30 (Amphasys AG, Switzerland). A traditional toxicity assay, Trypan Blue Dye Exclusion assay, and dark-field microscopy were used to validate the IFC method. Results: Spherical Ag particles (NM-300K) showed the highest toxic effect on U937 cells followed by ZnO (NM-111 ≥ NM-110) particles. Silica particles were moderate to non-toxic at all used concentrations under these conditions. A higher toxic effect was seen with smaller sized TiO2 particles (NM-101) compared to their larger analogues (NM-100). No interferences between the IFC and the used NMs were seen. Uptake and internalization of NMs were observed after 24 hours exposure, confirming actual NM-cell interactions. Conclusion: Results collected with the IFC demonstrate the applicability of this method for rapid nanotoxicity assessment, which proved to be less prone to nano-related interference issues compared to some traditional toxicity assays. Furthermore, this label-free and novel technique shows good potential for up-scaling in directions of an automated high-throughput screening and for future NM toxicity assessment. This work was supported by the EC FP7 NANoREG (Grant Agreement NMP4-LA-2013-310584), the Research Council of Norway, project NorNANoREG (239199/O70), the EuroNanoMed II 'GEMN' project (246672), and the UH-Nett Vest project.

Keywords: cytotoxicity, high-throughput, impedance, nanomaterials

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Authors: Gizem Eser Erdek

Abstract:

This study is research on predicting the remaining life of industrial cutting tools used in the industrial production process with deep learning methods. When the life of cutting tools decreases, they cause destruction to the raw material they are processing. This study it is aimed to predict the remaining life of the cutting tool based on the damage caused by the cutting tools to the raw material. For this, hole photos were collected from the hole-drilling machine for 8 months. Photos were labeled in 5 classes according to hole quality. In this way, the problem was transformed into a classification problem. Using the prepared data set, a model was created with convolutional neural networks, which is a deep learning method. In addition, VGGNet and ResNet architectures, which have been successful in the literature, have been tested on the data set. A hybrid model using convolutional neural networks and support vector machines is also used for comparison. When all models are compared, it has been determined that the model in which convolutional neural networks are used gives successful results of a %74 accuracy rate. In the preliminary studies, the data set was arranged to include only the best and worst classes, and the study gave ~93% accuracy when the binary classification model was applied. The results of this study showed that the remaining life of the cutting tools could be predicted by deep learning methods based on the damage to the raw material. Experiments have proven that deep learning methods can be used as an alternative for cutting tool life estimation.

Keywords: classification, convolutional neural network, deep learning, remaining life of industrial cutting tools, ResNet, support vector machine, VggNet

Procedia PDF Downloads 74

Authors: Tannaz Alimardani, Amirhossein Moghanian, Morteza Elsa

Abstract:

Bioactive glasses (BGs) are a group of surface-reactive biomaterials used in clinical applications as implants or filler materials in the human body to repair and replace diseased or damaged bone. Sol-gel technique was employed to prepare a SiO₂-CaO-P₂O₅ glass with a nominal composition of 58S BG with the addition of Sr and Li modifiers which imparts special properties to the BG. The effect of simultaneous addition of Sr and Li on bioactivity and biocompatibility, proliferation, alkaline phosphatase (ALP) activity of osteoblast cell line MC3T3-E1 and antibacterial property against methicillin-resistant Staphylococcus aureus (MRSA) bacteria were examined. BGs were characterized by X-ray diffraction, Fourier transform infrared spectroscopy and scanning electron microscopy before and after soaking the samples in the simulated body fluid (SBF) for different time intervals to characterize the formation of hydroxyapatite (HA) formed on the surface of BGs. Structural characterization indicated that the simultaneous presence of 5% Sr and 5% Li in 58S-BG composition not only did not retard HA formation because of the opposite effect of Sr and Li of the dissolution of BG in the SBF, but also stimulated the differentiation and proliferation of MC3T3-E1s. Moreover, the presence of Sr and Li on the dissolution of the ions resulted in an increase in the mean number of DAPI-labeled nuclei which was in good agreement with the live/dead assay. The result of antibacterial tests revealed that Sr and Li-substituted 58S bioactive glass exhibited a potential antibacterial effect against MRSA bacteria. Because of optimal proliferation and ALP activity of MC3T3-E1cells, proper bioactivity and high antibacterial potential against MRSA, BG-5/5 is suggested as a multifunctional candidate for bone tissue engineering.

Keywords: alkaline, alkaline earth, bioglass, co-doping, ion release

Procedia PDF Downloads 211

Authors: Syed Asif Hassan, Tabrej Khan

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Multiple sclerosis (MS) is a chronic demyelinating autoimmune disorder, of the central nervous system (CNS). In the present scenario, the current therapies either do not halt the progression of the disease or have side effects which limit the usage of current Disease Modifying Therapies (DMTs) for a longer period of time. Therefore, keeping the current treatment failure schema, we are focusing on screening novel analogues of the available DMTs that specifically bind and inhibit the Sphingosine1-phosphate receptor1 (S1PR1) thereby hindering the lymphocyte propagation toward CNS. The novel drug-like analogs molecule will decrease the frequency of relapses (recurrence of the symptoms associated with MS) with higher efficacy and lower toxicity to human system. In this study, an integrated approach involving ligand-based virtual screening protocol (Ultrafast Shape Recognition with CREDO Atom Types (USRCAT)) to identify the non-toxic drug like analogs of the approved DMTs were employed. The potency of the drug-like analog molecules to cross the Blood Brain Barrier (BBB) was estimated. Besides, molecular docking and simulation using Auto Dock Vina 1.1.2 and GOLD 3.01 were performed using the X-ray crystal structure of Mtb LprG protein to calculate the affinity and specificity of the analogs with the given LprG protein. The docking results were further confirmed by DSX (DrugScore eXtented), a robust program to evaluate the binding energy of ligands bound to the ligand binding domain of the Mtb LprG lipoprotein. The ligand, which has a higher hypothetical affinity, also has greater negative value. Further, the non-specific ligands were screened out using the structural filter proposed by Baell and Holloway. Based on the USRCAT, Lipinski’s values, toxicity and BBB analysis, the drug-like analogs of fingolimod and BG-12 showed that RTL and CHEMBL1771640, respectively are non-toxic and permeable to BBB. The successful docking and DSX analysis showed that RTL and CHEMBL1771640 could bind to the binding pocket of S1PR1 receptor protein of human with greater affinity than as compared to their parent compound (Fingolimod). In this study, we also found that all the drug-like analogs of the standard MS drugs passed the Bell and Holloway filter.

Keywords: antagonist, binding affinity, chemotherapeutics, drug-like, multiple sclerosis, S1PR1 receptor protein

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Authors: Sajjad Esmaeili Aghdam

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Economics typically conceptualizes individual behavior as the consequence of external states, for example, budgets and prices (or respective beliefs) and choices. As the main goal, we focus on the influence of a range of Behavioral Economics factors on Strategies of Digital Marketing, evaluation of strategies and deformation of it into highly prospective marketing strategies. The different forms of behavioral prospects all lead to the succeeding two main results. First, the steadiness of the economic dynamics in a currency union be contingent fatefully on the level of economic incorporation. More economic incorporation leads to more steady economic dynamics. Electronic word-of-mouth (eWOM) is “all casual communications focused at consumers through Internet-based technology connected to the usage or characteristics of specific properties and services or their venders.” eWOM can take many methods, the most significant one being online analyses. Writing this paper, 72 articles have been gathered, focusing on the title and the aim of the article from research search engines like Google Scholar, Web of Science, and PubMed. Recent research in strategic management and marketing proposes that markets should not be viewed as a given and deterministic setting, exogenous to the firm. Instead, firms are progressively abstracted as dynamic inventors of market prospects. The use of new technologies touches all spheres of the modern lifestyle. Social and economic life becomes unbearable without fast, applicable, first-class and fitting material. Psychology and economics (together known as behavioral economics) are two protruding disciplines underlying many theories in marketing. The wide marketing works papers consumers’ none balanced behavior even though behavioral biases might not continuously be steadily called or officially labeled.

Keywords: behavioral economics, digital marketing, marketing strategy, high impact strategies

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Authors: Daniella L. Pereira, Emeliana G. Imperial, Ingrid Webster, Ian Wiid, Hans Strijdom, Nireshni Chellan, Sanet H. Kotzé

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Rooibos (Aspalathus linearis) is a shrub-like bush native to the Western Cape of South Africa and commonly consumed as a herbal tea. Interest on the anti-oxidant capabilities of the tea have risen based on anecdotal evidence. Rooibos contains polyphenols that contribute to the overall antioxidant capacity of the tea. These polyphenols have been reported to attenuate the effects of oxidative stress in biological systems. The bioavailability of these compounds is compromised when exposed to light, pH fluctuations, and oxidation. It is crucial to evaluate whether the polyphenols in a typical rooibos solution remain constant over time when administered to rats in a research environment. This study aimed to determine the effects of various storage scenarios on the phenolic composition of rooibos tea commonly administered to rodents in experimental studies. A standardised aqueous solution of rooibos tea was filtered and divided into three samples namely fresh, refrigerated, and frozen. Samples were stored in air tight, light excluding bottles. Refrigerated samples were stored at 4°C for seven days. Frozen samples were stored for fourteen days at -20°C. Each sample consisted of two subgroups labeled day 1 and day 7. Teas marked day 7 of each group were kept in air tight, light protected bottles at room temperature for an additional week. All samples (n=6) were freeze-dried and underwent polyphenol characterization using liquid chromatography-mass spectrometry. The phenolic composition remained constant throughout all groups. This indicates that rooibos tea can be safely stored at the above conditions without compromising the phenolic viability of the tea typically used for research purposes.

Keywords: Aspalathus linearis, experimental studies, polyphenols, storage

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Authors: Qingsong Xiong, Cheng Yuan, Qingzhao Kong, Haibei Xiong

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Deep-learning-driven approaches based on vibration responses have attracted larger attention in rapid structural condition assessment while obtaining sufficient measured training data with corresponding labels is relevantly costly and even inaccessible in practical engineering. This study proposes an integrated label propagation network for structural condition assessment, which is able to diffuse the labels from continuously-generating measurements by intact structure to those of missing labels of damage scenarios. The integrated network is embedded with damage-sensitive features extraction by deep autoencoder and pseudo-labels propagation by optimized fuzzy clustering, the architecture and mechanism which are elaborated. With a sophisticated network design and specified strategies for improving performance, the present network achieves to extends the superiority of self-supervised representation learning, unsupervised fuzzy clustering and supervised classification algorithms into an integration aiming at assessing damage conditions. Both numerical simulations and full-scale laboratory shaking table tests of a two-story building structure were conducted to validate its capability of detecting post-earthquake damage. The identifying accuracy of a present network was 0.95 in numerical validations and an average 0.86 in laboratory case studies, respectively. It should be noted that the whole training procedure of all involved models in the network stringently doesn’t rely upon any labeled data of damage scenarios but only several samples of intact structure, which indicates a significant superiority in model adaptability and feasible applicability in practice.

Keywords: autoencoder, condition assessment, fuzzy clustering, label propagation

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Authors: Ahmed M. Debela, Mayreli Ortiz , Ciara K. O´Sullivan

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The completion of the human genome Project (HGP) has paved the way for mapping the diversity in the overall genome sequence which helps to understand the genetic causes of inherited diseases and susceptibility to drugs or environmental toxins. Arrayed primer extension (APEX) is a microarray based minisequencing strategy for screening disease causing mutations. It is derived from Sanger DNA sequencing and uses fluorescently dideoxynucleotides (ddNTPs) for termination of a growing DNA strand from a primer with its 3´- end designed immediately upstream of a site where single nucleotide polymorphism (SNP) occurs. The use of DNA polymerase offers a very high accuracy and specificity to APEX which in turn happens to be a method of choice for multiplex SNP detection. Coupling the high specificity of this method with the high sensitivity, low cost and compatibility for miniaturization of electrochemical techniques would offer an excellent platform for detection of mutation as well as sequencing of DNA templates. We are developing an electrochemical APEX for the analysis of SNPs found in the MYH7 gene for group of cardiomyopathy patients. ddNTPs were labeled with four different redox active compounds with four distinct potentials. Thiolated oligonucleotide probes were immobilised on gold and glassy carbon substrates which are followed by hybridisation with complementary target DNA just adjacent to the base to be extended by polymerase. Electrochemical interrogation was performed after the incorporation of the redox labelled dedioxynucleotide. The work involved the synthesis and characterisation of the redox labelled ddNTPs, optimisation and characterisation of surface functionalisation strategies and the nucleotide incorporation assays.

Keywords: array based primer extension, labelled ddNTPs, electrochemical, mutations

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Authors: Nasim Eslamirad, Mahdi Rasoulinezhad, Francesco De Luca, Sadok Ben Yahia, Kimmo Sakari Lylykangas, Francesco Pilla

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With the ongoing urbanization, cities face increasing environmental challenges impacting human well-being. To tackle these issues, data-driven approaches in urban analysis have gained prominence, leveraging urban data to promote sustainability. Integrating Machine Learning techniques enables researchers to analyze and predict complex environmental phenomena like Urban Heat Island occurrences in urban areas. This paper demonstrates the implementation of data-driven approach and interpretable Machine Learning algorithms with interpretability techniques to conduct comprehensive data analyses for sustainable urban design. The developed framework and algorithms are demonstrated for Tallinn, Estonia to develop sustainable urban strategies to mitigate urban heat waves. Geospatial data, preprocessed and labeled with UHI levels, are used to train various ML models, with Logistic Regression emerging as the best-performing model based on evaluation metrics to derive a mathematical equation representing the area with UHI or without UHI effects, providing insights into UHI occurrences based on buildings and urban features. The derived formula highlights the importance of building volume, height, area, and shape length to create an urban environment with UHI impact. The data-driven approach and derived equation inform mitigation strategies and sustainable urban development in Tallinn and offer valuable guidance for other locations with varying climates.

Keywords: data-driven approach, machine learning transparent models, interpretable machine learning models, urban heat island effect

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Authors: Chua Bee Seok, Getrude Cosmas, Jasmine Adela Mutang, Shazia Iqbal Hashmi

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The aims of this study were to determine the factor structure and psychometric properties (i.e., reliability and convergent validity) of the employees trust scale, a newly created instrument by the researchers. The employees trust scale initially contained 82 items to measure employee’s trust toward their supervisors. A sample of 818 (343 females, 449 males) employees were selected randomly from public and private organization sectors in Kota Kinabalu, Sabah, Malaysia. Their ages ranged from 19 to 67 years old with the mean of 34.55 years old. Their average tenure with their current employer was 11.2 years (s.d. = 7.5 years). The respondents were asked to complete the employees trust scale, as well as a managerial trust questionnaire from Mishra. The exploratory factor analysis on employee’s trust toward their supervisor’s extracted three factors, labeled 'trustworthiness' (32 items), 'position status' (11 items) and 'relationship' (6 items) which accounted for 62.49% of the total variance. Trustworthiness factors were re-categorized into three sub factors: competency (11 items), benevolence (8 items) and integrity (13 items). All factors and sub factors of the scales demonstrated clear reliability with internal consistency of Cronbach’s Alpha above 0.85. The convergent validity of the Scale was supported by an expected pattern of correlations (positive and significant correlation) between the score of all factors and sub factors of the scale and the score on the managerial trust questionnaire which measured the same construct. The convergent validity of employees trust scale was further supported by the significant and positive inter correlation between the factors and sub factors of the scale. The results suggest that the employees trust scale is a reliable and valid measure. However, further studies need to be carried out in other groups of sample as to further validate the Scale.

Keywords: employees trust scale, psychometric properties, trustworthiness, position status, relationship

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Authors: Danielle Shackley, Yetunde Folajimi

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As more people turn to the internet seeking health-related information, there is more risk of finding false, inaccurate, or dangerous information. Sentiment analysis is a natural language processing technique that assigns polarity scores to text, ranging from positive, neutral, and negative. In this research, we evaluate the weight of a sentiment analysis feature added to fake health news classification models. The dataset consists of existing reliably labeled health article headlines that were supplemented with health information collected about COVID-19 from social media sources. We started with data preprocessing and tested out various vectorization methods such as Count and TFIDF vectorization. We implemented 3 Naive Bayes classifier models, including Bernoulli, Multinomial, and Complement. To test the weight of the sentiment analysis feature on the dataset, we created benchmark Naive Bayes classification models without sentiment analysis, and those same models were reproduced, and the feature was added. We evaluated using the precision and accuracy scores. The Bernoulli initial model performed with 90% precision and 75.2% accuracy, while the model supplemented with sentiment labels performed with 90.4% precision and stayed constant at 75.2% accuracy. Our results show that the addition of sentiment analysis did not improve model precision by a wide margin; while there was no evidence of improvement in accuracy, we had a 1.9% improvement margin of the precision score with the Complement model. Future expansion of this work could include replicating the experiment process and substituting the Naive Bayes for a deep learning neural network model.

Keywords: sentiment analysis, Naive Bayes model, natural language processing, topic analysis, fake health news classification model

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Authors: Abdullah Ijaz Hussain

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The purpose of this study was to explore the cardioprotective and anti-inflammatory effects of polyphenol-rich extracts from cucurbitaceae family members, including Cucurbita pepo, C. moschata, and C. maxima, on rat models. The initial crude extracts from these cucurbits were further separated into hexane, chloroform, ethyl acetate, butanol, and aqueous ethanol fractions, labeled as HEF, CHF, EAF, BUF, and AEF, respectively. Of these, AEF yielded the highest amount, followed by BUF, HEF, EAF, and CHF in descending order. Notably, EAF contained the greatest concentration of total phenolics, flavonoids, and flavonols. In terms of antioxidant activity, EAF demonstrated the most potent DPPH radical scavenging capability, succeeded by CHF, BUF, AEF, and HEF. EAF also exhibited the strongest reducing potential among the fractions. RP-HPLC analysis identified various phenolic acids and flavonoids across the cucurbita fractions, including ferulic acid, vanillic acid, p-coumeric acid, gallic acid, p-hydroxybenzoic acid, chlorogenic acid, catechin, rutin, quercetin, myricetin, and kaempferol. Doses of 250 and 500 mg/kg body weight of cucurbita fractions were administered orally to male WKY rats daily for 21 days. The rats' body weight, heart rate, and blood pressure were monitored bi-weekly. Oxidative status assessments were conducted using plasma samples to measure levels of malondialdehyde (MDA), superoxide dismutase (SOD), reduced glutathione (GSH), nitric oxide (NO), and total antioxidant capacity (TAC). At the study's conclusion, surgical assessments, including blood pressure, pulse wave velocity (PWV), and echocardiograms (ECG) were performed. The findings indicated that EAF from cucurbita significantly enhanced antihypertensive and antioxidant activities in the SHR rat group.

Keywords: polyphenols, chlorogenic acid, antihypertensive activity, oxidative stress, lcms

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Authors: Abeer A. Aljohani

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COVID-19 virus spread has been one of the extreme pandemics across the globe. It is also referred to as coronavirus, which is a contagious disease that continuously mutates into numerous variants. Currently, the B.1.1.529 variant labeled as omicron is detected in South Africa. The huge spread of COVID-19 disease has affected several lives and has surged exceptional pressure on the healthcare systems worldwide. Also, everyday life and the global economy have been at stake. This research aims to predict COVID-19 disease in its initial stage to reduce the death count. Machine learning (ML) is nowadays used in almost every area. Numerous COVID-19 cases have produced a huge burden on the hospitals as well as health workers. To reduce this burden, this paper predicts COVID-19 disease is based on the symptoms and medical history of the patient. This research presents a unique architecture for COVID-19 detection using ML techniques integrated with feature dimensionality reduction. This paper uses a standard UCI dataset for predicting COVID-19 disease. This dataset comprises symptoms of 5434 patients. This paper also compares several supervised ML techniques to the presented architecture. The architecture has also utilized 10-fold cross validation process for generalization and the principal component analysis (PCA) technique for feature reduction. Standard parameters are used to evaluate the proposed architecture including F1-Score, precision, accuracy, recall, receiver operating characteristic (ROC), and area under curve (AUC). The results depict that decision tree, random forest, and neural networks outperform all other state-of-the-art ML techniques. This achieved result can help effectively in identifying COVID-19 infection cases.

Keywords: supervised machine learning, COVID-19 prediction, healthcare analytics, random forest, neural network

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Authors: Irina S. Kolesnikova, Alexander A. Dolskiy, Natalya A. Lemskaya, Yulia V. Maksimova, Asia R. Shorina, Alena S. Telepova, Alexander S. Graphodatsky, Dmitry V. Yudkin

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A cytogenetic and molecular genetic study of the family with a male child who had mental retardation and autistic features revealed an abnormal chromosome 13 bearing an enlarged p-arm with amplified ribosomal DNA (rDNA) in a boy and his father. Cytogenetic analysis using standard G-banding and FISH with labeled rDNA probes revealed an abnormal chromosome 13 with an enlarged p-arms due to rDNA amplification in a male child, who had clinically confirmed mental retardation and an autistic behavior. This chromosome is evidently inherited from the father, who has morphologically the same chromosome, but is healthy. The karyotype of the mother was normal. Ag-NOR staining showed brightly stained large whole-p-arm nucleolus organizer regions (NORs) in a child and normal-sized NORs in his father with 13p+-NOR-amount mosaicism. qRT-PCR with specific primers showed highly increased levels of 18S, 28S and 5,8 S ribosomal RNA (rRNA) in the patient’s blood samples compared to a normal healthy control donor. Both patient’s father and mother had no elevated levels of rRNAs expression. Thus, in this case, rRNA level seems to correlate with mental retardation in familial individuals with 13p+. Our findings of rRNA overexpression in a patient with mental retardation and his parents may show a possible link between the karyotype (p-arm enlargement due to rDNA amplification), rDNA functionality (rRNA overexpression), functional changes in the brain and mental retardation. The study is supported by Russian Science Foundation Grant 15-15-10001.

Keywords: mental retardation, ribosomal DNA–rDNA, ribosomal RNA–rRNA, nucleolus organizer region–NOR, chromosome 13

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