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1. Probabilities for asymmetric p-outside values

Author

Jordanova, Pavlina K.

Subjects
Statistics - Methodology, 60E05 60E05 62E15, 62F10, 60E05
Abstract

In 2017-2020 Jordanova and co-authors investigate probabilities for p-outside values and determine them in many particular cases. They show that these probabilities are closely related to the concept for heavy tails. Tukey's boxplots are very popular and useful in practice. Analogously to the chi-square-criterion, the relative frequencies of the events an observation to fall in different their parts, compared with the corresponding probabilities an observation of a fixed probability distribution to fall in the same parts, help the practitioners to find the accurate probability distribution of the observed random variable. These open the door to work with the distribution sensitive estimators which in many cases are more accurate, especially for small sample investigations. All these methods, however, suffer from the disadvantage that they use inter quantile range in a symmetric way. The concept for outside values should take into account the form of the distribution. Therefore, here, we give possibility for more asymmetry in analysis of the tails of the distributions. We suggest new theoretical and empirical box-plots and characteristics of the tails of the distributions. These are theoretical asymmetric p-outside values functions. We partially investigate some of their properties and give some examples. It turns out that they do not depend on the center and the scaling factor of the distribution. Therefore, they are very appropriate for comparison of the tails of the distribution, and later on, for estimation of the parameters, which govern the tail behaviour of the cumulative distribution function., Comment: This work is presented on MATHTECH (MATTEX in Bulgarian) 24-26 October 2024, Konstantin Preslavsky University, Shumen, Bulgaria

Published
2024

2. Prediction of the SYM-H Index Using a Bayesian Deep Learning Method with Uncertainty Quantification

Author

Abduallah, Yasser, Alobaid, Khalid A., Wang, Jason T. L., Wang, Haimin, Jordanova, Vania K., Yurchyshyn, Vasyl, Cavus, Huseyin, and Jing, Ju

Subjects
Astrophysics - Instrumentation and Methods for Astrophysics, Computer Science - Machine Learning
Abstract

We propose a novel deep learning framework, named SYMHnet, which employs a graph neural network and a bidirectional long short-term memory network to cooperatively learn patterns from solar wind and interplanetary magnetic field parameters for short-term forecasts of the SYM-H index based on 1-minute and 5-minute resolution data. SYMHnet takes, as input, the time series of the parameters' values provided by NASA's Space Science Data Coordinated Archive and predicts, as output, the SYM-H index value at time point t + w hours for a given time point t where w is 1 or 2. By incorporating Bayesian inference into the learning framework, SYMHnet can quantify both aleatoric (data) uncertainty and epistemic (model) uncertainty when predicting future SYM-H indices. Experimental results show that SYMHnet works well at quiet time and storm time, for both 1-minute and 5-minute resolution data. The results also show that SYMHnet generally performs better than related machine learning methods. For example, SYMHnet achieves a forecast skill score (FSS) of 0.343 compared to the FSS of 0.074 of a recent gradient boosting machine (GBM) method when predicting SYM-H indices (1 hour in advance) in a large storm (SYM-H = -393 nT) using 5-minute resolution data. When predicting the SYM-H indices (2 hours in advance) in the large storm, SYMHnet achieves an FSS of 0.553 compared to the FSS of 0.087 of the GBM method. In addition, SYMHnet can provide results for both data and model uncertainty quantification, whereas the related methods cannot., Comment: 28 pages, 8 figures

Published
2024

3. Mixed Poisson process with Min-U-Exp mixing variable

Author

Jordanova, Pavlina K., Veleva, Evelina, and Stehlik, Milan

Subjects
Mathematics - Probability, 60G10
Abstract

This work continues the research done in Jordanova and Veleva (2023) where the history of the problem could be found. In order to obtain the structure distribution of the newly-defined Mixed Poisson process, here the operation "max" is replaced with "min". We start with the definition of Min-U-Exp distribution. Then, we compute its numerical characteristics and investigate some of its properties. The joint distribution of the inter-arrival times (which are dependent) is the Multivariate Exp-Min-U-Exp distribution of $II^{-nd}$ kind. Its univariate and multivariate versions are described, and the formulae for their numerical characteristics are obtained. The distribution of the moments of arrival of different events is called Erlang-Min-U-Exp. Different properties of these distributions are obtained, and their numerical characteristics are computed. Multivariate ordered Mixed Poisson-Min-U-Exp distribution describes the joint distribution of the time-intersection of a Mixed Poisson process with Min-U-Exp mixing variable. The corresponding distribution of the additive increments (which are also dependent) is the Mixed Poisson-Min-U-Exp one. The considered relations between these distributions simplify their understanding., Comment: Work in progress. arXiv admin note: text overlap with arXiv:2307.09798

Published
2023

5. Mixed Poisson process with Max-U-Exp mixing variable -- Working version

Author

Jordanova, Pavlina K. and Veleva, Evelina

Subjects
Mathematics - Probability, 60J05
Abstract

This work defines and investigates the properties of the Max-U-Exp distribution. The method of moments is applied in order to estimate its parameters. Then, by using the previous general theory about Mixed Poisson processes, developed by Grandel (1997), and Karlis and Xekalaki (2005), and analogously to Jordanova et al. (2023), and Jordanova and Stehlik (2017) we define and investigate the properties of the new random vectors and random variables, which are related with this particular case of a Mixed Poisson process. Exp-Max-U-Exp distribution is defined and thoroughly investigated. It arises in a natural way as a distribution of the inter-arrival times in the Mixed Poisson process with Max-U-Exp mixing variable. The distribution of the renewal moments is called Erlang-Max-U-Exp and is defined via its probability density function. Investigation of its properties follows. Finally, the corresponding Mixed Poisson process with Max-U-Exp mixing variable is defined. Its finite dimensional and conditional distributions are found and their numerical characteristics are determined., Comment: The article has been accepted by AIP Conference Proceedings, 49th International Conference Applications of Mathematics in Engineering and Economics, 10 - 16 June 2023, Sozopol, Bulgaria. After it is published, it will be found at Link

Published
2023

9. Mixed Poisson process with Stacy mixing variable -- Working version

Author

Jordanova, Pavlina K., Savov, Mladen, Tchorbadjieff, Assen, and Stehlík, Milan

Subjects
Mathematics - Probability, 60G20
Abstract

Stacy distribution defined for the first time in 1961 provides a flexible framework for modelling of a wide range of real-life behaviours. It appears under different names in the scientific literature and contains many useful particular cases. Homogeneous Poisson processes are appropriate apriori models for the number of renewals up to a given time $t>0$. This paper mixes them and considers a Mixed Poisson process with Stacy mixing variable. We call it a Poisson-Stacy process. The resulting counting process is one of the Generalised Negative Binomial processes, and the distribution of its time-intersections are very-well investigated in the scientific literature. Here we define and investigate their joint probability distributions. Then, the corresponding mixed renewal process is investigated and Exp-Stacy and Erlang-Stacy distributions are defined and partially studied. The paper finishes with a simulation study of these stochastic processes. Some plots of the probability density functions, probability mass functions, mean square regressions and sample paths are drawn together with the corresponding code for the simulations.

Published
2023

10. Bodies and Lives in Victorian England: Science, Sexuality, and the Affliction of Being Female

Author

Jordanova, Ludmilla

Subjects
Bodies and Lives in Victorian England: Science, Sexuality, and the Affliction of Being Female (Nonfiction work) -- Stone, Pamela K. -- Sanders, Lise Shapiro, Books -- Book reviews, Humanities, Social sciences
Abstract

Bodies and Lives in Victorian England: Science, Sexuality, and the Affliction of Being Female, by Pamela K. Stone and Lise Shapiro Sanders, pp. xii + 145. London and New York: [...]

Published
2024
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14. Addressing food insecurity in rural primary care: a mixed-methods evaluation of barriers and facilitators

Author

Kayla E. Jordanova, Arvind Suresh, Chelsey R. Canavan, Tiffany D’cruze, Alka Dev, Maureen Boardman, and Meaghan A. Kennedy

Subjects
Food insecurity, Primary care, Rural health, Social determinants of health, Medicine (General), R5-920
Abstract

Abstract Background Food insecurity (FI) is associated with negative health outcomes and increased healthcare utilization. Rural populations face increased rates of FI and encounter additional barriers to achieving food security. We sought to identify barriers and facilitators to screening and interventions for FI in rural primary care practices. Methods We conducted a mixed-methods study using surveys and semi-structured interviews of providers and staff members from rural primary care practices in northern New England. Survey data were analyzed descriptively, and thematic analysis was used to identify salient interview themes. Results Participants from 24 rural practices completed the survey, and 13 subsequently completed an interview. Most survey respondents (54%) reported their practices systematically screen for FI and 71% reported food needs were “very important” for their patients and communities. Time and resource constraints were the most frequently cited barriers to screening for and addressing FI in practices based on survey results. Interview themes were categorized by screening and intervention procedures, community factors, patient factors, external factors, practice factors, process and implementation factors, and impact of FI screening and interventions. Time and resource constraints were a major theme in interviews, and factors attributed to rural practice settings included geographically large service areas, stigma from loss of privacy in small communities, and availability of food resources through farming. Conclusions Rural primary care practices placed a high value on addressing food needs but faced a variety of barriers to implementing and sustaining FI screening and interventions. Strategies that utilize practice strengths and address time and resource constraints, stigma, and large service areas could promote the adoption of novel interventions to address FI.

Published
2024
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15. Bivariate Compound Poisson Risk Processes with Shocks

Author

Jordanova, Pavlina, Veleva, Evelina, and Mitov, Kosto

Subjects
Mathematics - Probability, 60G50, 60G70
Abstract

Contemporary insurance theory is concentrated on models with different types of polices and shock events may influence the payments on some of them. Jordanova (2018) considered a model where a shock event contributes to the total claim amount with one and the same value of the claim sizes to different types of polices. Jordanova and Veleva (2021) went a step closer to real-life situations and allowed a shock event to cause different claim sizes to different types of polices. In that paper, the counting process is assumed to be Multinomial. Here it is replaced with different independent homogeneous Poison processes. The bivariate claim counting process is expressed in two different ways. Its marginals and conditional distributions are totally described. The mean square regression of these processes is computed. The Laplace-Stieltjes transforms and numerical characteristics of the total claim amount processes are obtained. The risk reserve process and the probabilities of ruin in infinite time are discussed. The risk reserve just before the ruin and the deficit (or the severity) at ruin are thoroughly investigated in the case when the initial capital is zero. Their means, probability mass functions, and probability generating functions are obtained. Although the model is constructed by a multivariate counting process, along the paper it is shown that the total claim amount process is stochastically equivalent to a univariate compound Poisson process. These allow us to reduce the considered risk model to a Cramer-Lundberg risk model, to use the corresponding results, and to make the conclusions for the new model. Analogous results can be obtained for more types of polices and more types of shock events. The results are applied in case when the claim sizes are exponentially distributed. Stochastically equivalent models could be analogously constructed in queuing theory., Comment: The work is presented on Fourteenth Conference of the Euro-American Consortium for Promoting the Application of Mathematics in Technical and Natural Sciences, Albena, Bulgaria, June 22-27, 2022

Published
2022

17. Case report: First diagnosis of Fabry disease in North Macedonia in a patient presenting with kidney failure on hemodialysis

Author

Nikola Gjorgjievski, Vlatko Karanfilovski, Todor Arsov, Pavlina Dzekova Vidimliski, Galisna Severeova Andreevska, Gjulshen Selim, Petar Dejanov, Vasilena Jordanova, Ivelina Marinova, Emil Paskalev, and Igor G. Nikolov

Subjects
Fabry disease, chronic kidney disease, hemodialysis, α-galactosidase A, X-linked disorder, Genetics, QH426-470
Abstract

IntroductionFabry disease is a rare X-linked lysosomal storage disorder caused by α-galactosidase A (α-Gal A) deficiency. Reduced or absent enzyme activity causes progressive lysosomal accumulation of globotriaosylceramide (Lyso-Gb3) in various cells throughout the body to trigger inflammation and fibrosis.Case descriptionWe present the first familial case of Fabry Disease in North Macedonia identified based on clinical manifestations and confirmed through enzyme, biomarker, and genetic tests. The index case in the family was a 45-year-old male undergoing hemodialysis therapy. He has had chronic burning uncontrolled limb pain since childhood, intermittent abdominal cramps, anhidrosis, and hypertension. The constellation of clinical presentations accompanied by similar symptoms in close family members prompted the enzyme, biomarker, and genetic analyses for Fabry disease. Genetic testing identified a known pathogenic GLA missense variant c.443G>A or p.(Ser148Asn) in the hemizygous state. Subsequent family studies allowed identification of another hemizygous male and five heterozygous female carriers affected by this X-linked disorder.ConclusionWe report identification of the first familial case of Fabry disease in North Macedonia and describe the phenotype associated with the Ser148Asn GLA variant. Greater awareness of this rare disease linked to continuous medical education is crucial for timely diagnosis and treatment.

Published
2024
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18. Clinical and genetic variability among Bulgarian patients with autosomal recessive spastic ataxia of Charlevoix–Saguenay

Author

Teodora Chamova, Neviana Ivanova, Sylvia Cherninkova, Maya Koleva, Dora Zlatareva, Veneta Bojinova, Kalina Mihova, Martin Georgiev, Dilyan Ferdinandov, Stoyan Bichev, Radka Kaneva, Vanio Mitev, Albena Jordanova, and Ivailo Tournev

Subjects
ARSACS, Bulgarian patients, SACS gene, whole‐exome sequencing, Genetics, QH426-470
Abstract

Abstract Background Autosomal recessive spastic ataxia ofCharlevoix–Saguenay (ARSACS) is a rare neurodegenerative disorder characterizedby early‐onset cerebellar ataxia, peripheral sensorimotor neuropathy, and lowerlimb spasticity. We present clinical andgenetic data of the first Bulgarian patients diagnosed with ARSACS by wholeexome sequencing (WES). Methods Variant filtering was performed usinglocally established pipeline and the selected variants were analysed by Sangersequencing. All patients underwent clinical examination and testingincluding the standard rating scales for spastic paraplegia and ataxia. Results Five different SACS gene variants, three of which novel, have been identified inpatients from three different ethnic groups. In addition to the classicalclinical triad, brain MRI revealed cerebellar atrophy, linear pontineT2‐hypointensities, and hyperintense rim lateral tothalamus combined with retinal nerve fiber layer thickening on opticcoherence tomography (OCT). Conclusion We expand the mutation, geographic, and phenotypic spectrum of ARSACS, adding Bulgaria to the world map of the disease, and drawing attention to the fact that it is still misdiagnosed. We demonstrated that brain MRI and OCT are necessary clinical tests for ARSACS diagnosis, even if one of the cardinal clinical features is lacking

Published
2024
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19. Predicting Solar Energetic Particles Using SDO/HMI Vector Magnetic Data Products and a Bidirectional LSTM Network

Author

Abduallah, Yasser, Jordanova, Vania K., Liu, Hao, Li, Qin, Wang, Jason T. L., and Wang, Haimin

Subjects
Astrophysics - Solar and Stellar Astrophysics, Computer Science - Machine Learning
Abstract

Solar energetic particles (SEPs) are an essential source of space radiation, which are hazards for humans in space, spacecraft, and technology in general. In this paper we propose a deep learning method, specifically a bidirectional long short-term memory (biLSTM) network, to predict if an active region (AR) would produce an SEP event given that (i) the AR will produce an M- or X-class flare and a coronal mass ejection (CME) associated with the flare, or (ii) the AR will produce an M- or X-class flare regardless of whether or not the flare is associated with a CME. The data samples used in this study are collected from the Geostationary Operational Environmental Satellite's X-ray flare catalogs provided by the National Centers for Environmental Information. We select M- and X-class flares with identified ARs in the catalogs for the period between 2010 and 2021, and find the associations of flares, CMEs and SEPs in the Space Weather Database of Notifications, Knowledge, Information during the same period. Each data sample contains physical parameters collected from the Helioseismic and Magnetic Imager on board the Solar Dynamics Observatory. Experimental results based on different performance metrics demonstrate that the proposed biLSTM network is better than related machine learning algorithms for the two SEP prediction tasks studied here. We also discuss extensions of our approach for probabilistic forecasting and calibration with empirical evaluation., Comment: 22 pages, 6 figures, 8 tables

Published
2022
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20. Association of BMI, lipid-lowering medication, and age with prevalence of type 2 diabetes in adults with heterozygous familial hypercholesterolaemia: a worldwide cross-sectional study

Author

Elshorbagy, Amany, Lyons, Alexander R.M., Vallejo-Vaz, Antonio J., Stevens, Christophe A.T., Dharmayat, Kanika I., Brandts, Julia, Catapano, Alberico L., Freiberger, Tomas, Hovingh, G. Kees, Mata, Pedro, Raal, Frederick J., Santos, Raul D., Soran, Handrean, Watts, Gerald F., Abifadel, Marianne, Aguilar-Salinas, Carlos A., Alhabib, Khalid F., Alkhnifsawi, Mutaz, Almahmeed, Wael, Alonso, Rodrigo, Al-Rasadi, Khalid, Al-Sarraf, Ahmad, Ashavaid, Tester F., Banach, Maciej, Binder, Christoph J., Bourbon, Mafalda, Brunham, Liam R., Chlebus, Krzysztof, Corral, Pablo, Cruz, Diogo, Davletov, Kairat, Descamps, Olivier S., Ezhov, Marat, Gaita, Dan, Groselj, Urh, Harada-Shiba, Mariko, Holven, Kirsten B., Kayikcioglu, Meral, Khovidhunkit, Weerapan, Lalic, Katarina, Latkovskis, Gustavs, Laufs, Ulrich, Liberopoulos, Evangelos, Lima-Martinez, Marcos M., Lin, Jie, Maher, Vincent, Marais, A. David, März, Winfried, Mirrakhimov, Erkin, Miserez, André R., Mitchenko, Olena, Nawawi, Hapizah, Nordestgaard, Børge G., Panayiotou, Andrie G., Paragh, György, Petrulioniene, Zaneta, Pojskic, Belma, Postadzhiyan, Arman, Reda, Ashraf, Reiner, Željko, Reyes, Ximena, Sadiq, Fouzia, Sadoh, Wilson E., Schunkert, Heribert, Shek, Aleksandr B., Stroes, Erik, Su, Ta-Chen, Subramaniam, Tavintharan, Susekov, Andrey V., Tilney, Myra, Tomlinson, Brian, Truong, Thanh-Huong, Tselepis, Alexandros D., Tybjærg-Hansen, Anne, Vázquez, Alejandra C., Viigimaa, Margus, Vohnout, Branislav, Wang, Luya, Yamashita, Shizuya, Arca, Marcello, Averna, Maurizio, Schreier, Laura, Pang, Jing, Ebenbichler, Christoph, Dieplinger, Hans, Innerhofer, Reinhold, Winhofer-Stöckl, Yvonne, Greber-Platzer, Susanne, Krychtiuk, Konstantin, Speidl, Walter, Toplak, Hermann, Widhalm, Kurt, Stulnig, Thomas, Huber, Kurt, Höllerl, Florian, Rega-Kaun, Gersina, Kleemann, Lucas, Mäser, Martin, Scholl-Bürgi, Sabine, Säly, Christoph, Mayer, Florian J., Sperone, Alexandra, Tanghe, Chloé, Gérard, Anne-Catherine, Pojskic, Lamija, Sisic, Ibrahim, Durak Nalbantic, Azra, Ejubovic, Malik, Jannes, Cinthia E., Pereira, Alexandre C., Krieger, Jose E., Petrov, Ivo, Goudev, Assen, Nikolov, Fedya, Tisheva, Snejana, Yotov, Yoto, Tzvetkov, Ivajlo, Baass, Alexis, Bergeron, Jean, Bernard, Sophie, Brisson, Diane, Cermakova, Lubomira, Couture, Patrick, Francis, Gordon A., Gaudet, Daniel, Hegele, Robert A., Khoury, Etienne, Mancini, G.B. John, McCrindle, Brian W., Paquette, Martine, Ruel, Isabelle, Iatan, Iulia, Cuevas, Ada, Wang, Xumin, Meng, Kang, Song, Xiantao, Yong, Qiang, Jiang, Tao, Liu, Ziyou, Duan, Yanyu, Hong, Jing, Ye, Pucong, Chen, Yan, Qi, Jianguang, Liu, Zesen, Li, Yuntao, Zhang, Chaoyi, Peng, Jie, Yang, Ya, Yu, Wei, Wang, Qian, Yuan, Hui, Cheng, Shitong, Jiang, Long, Chong, Mei, Jiao, Jian, Wu, Yue, Wen, Wenhui, Xu, Liyuan, Zhang, Ruiying, Qu, Yichen, He, Jianxun, Fan, Xuesong, Wang, Zhenjia, Chow, Elaine, Pećin, Ivan, Perica, Dražen, Symeonides, Phivos, Vrablik, Michal, Ceska, Richard, Soska, Vladimir, Tichy, Lukas, Adamkova, Vera, Franekova, Jana, Cifkova, Renata, Kraml, Pavel, Vonaskova, Katerina, Cepova, Jana, Dusejovska, Magdalena, Pavlickova, Lenka, Blaha, Vladimir, Rosolova, Hana, Nussbaumerova, Barbora, Cibulka, Roman, Vaverkova, Helena, Cibickova, Lubica, Krejsova, Zdenka, Rehouskova, Katerina, Malina, Pavel, Budikova, Milena, Palanova, Vaclava, Solcova, Lucie, Lubasova, Alena, Podzimkova, Helena, Bujdak, Juraj, Vesely, Jiri, Jordanova, Marta, Salek, Tomas, Urbanek, Robin, Zemek, Stanislav, Lacko, Jan, Halamkova, Hana, Machacova, Sona, Mala, Sarka, Cubova, Eva, Valoskova, Katerina, Burda, Lukas, Benn, Marianne, Bendary, Ahmed, Daoud, Ihab, Emil, Sameh, Elbahry, Atef, Rafla, Samir, Sanad, Osama, Kazamel, Ghada, Ashraf, Dr Mohamed, Sobhy, Mohamed, El-Hadidy, Amro, Shafy, Mohamed Abdoul, Kamal, Saif, Bendary, Mohamed, Talviste, Grete, Christmann, Jutta, Dressel, Alexander, Fath, Felix, Ferraro, Chiara, Frenzke, Lydia, Gopon, Alica, Klein, Isabel, Pienkowska, Dominika, Sietmann, Tobias, Sonntag, Antonia, Adjan, Omar, Bahrmann, Philipp, Baessler, Andrea, Barkowski, Rasmus, Beckerdjian, Raffi, Berr, Christina, Birkenfeld, Andreas, Böll, Gereon, Carstensen, Avisha, Demuth, Ilya, Finkernagel, Holger, Gouni-Berthold, Ioanna, Hahmann, Harry, Hamerle, Michael, Halder, Julian, Heide, Maria, Julius, Ulrich, Kassner, Ursula, Katzmann, Julius L, Kirschbaum, Anja, Klose, Gerald, Könemann, Stephanie, König, Christel, König, Wolfgang, Krämer, Bernhard, Kuprat, Gerrit, Koschker, Ann-Cathrin, Kilic, Özlem, Lindenmeier, Gerd, Van de Loo, Iris, Lorenz, Babette, Lorenz, Elke, Löhr, Birgit, McChord, Johanna, Maslarska, Mariya, Methe, Heiko, Merkel, Martin, Moussaoui, Zineb, Müller-Kozarez, Irina, Olivier, Christoph B, Ong, Peter, Otte, Britta, Parhofer, Klaus, Partsch, Carl-Joachim, Paulus, Michael, Pehlivanli, Sinan, Pflederer, Tobias, Pusl, Thomas, Richter, Veronika, Rosner, Stefanie, Sanin, Veronika, Schäfer, Sebastian, Schäfer, Christoph, Schatz, Ulrike, Schirmer, Stephan, Schmidt, Christine, Seeger, Wolfgang, Sisovic, Snezna, Spens, Antje, Jablonski, Ksenija Stach, Stadelmann, Alexander, Steinhagen-Thiessen, Elisabeth, Stürzebecher, Paulina, Tafelmeier, Maria, Tillack, Dörthe, Tselmin, Sergey, Tünnemann-Tarr, Adrienn, Vogt, Anja, Beckerath, Jens von, Wilke, Andreas, Wolf, Ulrich, Zemmrich, Claudia, Rizos, Christos V., Skoumas, Ioannis, Tziomalos, Konstantinos, Rallidis, Loukianos, Kotsis, Vasileios, Doumas, Michalis, Athyros, Vasileios, Skalidis, Emmanouil, Kolovou, Genovefa, Kolovou, Vana, Garoufi, Anastasia, Bilianou, Eleni, Koutagiar, Iosif, Kiouri, Estela, Antza, Christina, Zacharis, Evangelos, Attilakos, Achilleas, Sfikas, George, Koumaras, Charalambos, Anagnostis, Panagiotis, Anastasiou, Georgia, Liamis, George, Koutsogianni, Amalia-Despoina, Petkou, Ermioni, Milionis, Haralambos, Koulouri, Anastasia, Prodromiadou, Elisavet, Karányi, Zsolt, Harangi, Mariann, Bajnok, László, Audikovszky, Mária, Márk, László, Benczúr, Béla, Reiber, István, Nagy, Gergely, Nagy, András, Reddy, Lakshmi Lavanya, Shah, Swarup A. V, Ponde, Chandrashekhar K., Dalal, Jamshed J., Sawhney, Jitendra P.S., Verma, Ishwar C., Altaey, Mays, Al-Jumaily, Khalid, Rasul, Dilshad, Abdalsahib, Ali Fawzi, Jabbar, Amer Abdl, Al-ageedi, Mohanad, Dhamin, Mohammed, AlFil, Sarmad, Khadhim, Foad, Miahy, Sabah, Agar, Ruth, Catapano, Alberico Luigi, Calandra, Sebastiano, Tarugi, Patrizia, Casula, Manuela, Galimberti, Federica, Olmastroni, Elena, Sarzani, Riccardo, Ferri, Claudio, Repetti, Elena, Piro, Salvatore, Suppressa, Patrizia, Meregalli, Giancarla, Borghi, Claudio, Muntoni, Sandro, Calabrò, Paolo, Cipollone, Francesco, Purrello, Francesco, Pujia, Arturo, Passaro, Angelina, Marcucci, Rossella, Pecchioli, Valerio, Pisciotta, Livia, Mandraffino, Giuseppe, Pellegatta, Fabio, Mombelli, Giuliana, Branchi, Adriana, Fiorenza, Anna Maria, Pederiva, Cristina, Werba, Josè Pablo, Parati, Gianfranco, Carubbi, Francesca, Iughetti, Lorenzo, Fortunato, Giuliana, Iannuzzi, Arcangelo, Iannuzzo, Gabriella, Cefalù, Angelo Baldassare, Biasucci, Giacomo, Zambon, Sabina, Pirro, Matteo, Sbrana, Francesco, Trenti, Chiara, D'Erasmo, Laura, Federici, Massimo, Ben, Maria Del, Bartuli, Andrea, Giaccari, Andrea, Pipolo, Antonio, Citroni, Nadia, Guardamagna, Ornella, Lia, Salvatore, Benso, Andrea, Biolo, Gianni, Maroni, Lorenzo, Lupi, Alessandro, Bonanni, Luca, Rinaldi, Elisabetta, Zenti, Maria Grazia, Matsuki, Kota, Hori, Mika, Ogura, Masatsune, Masuda, Daisaku, Kobayashi, Takuya, Nagahama, Kumiko, Al-Jarallah, Mohammed, Radovic, Mirjana, Lunegova, Olga, Bektasheva, Erkayim, Abilova, Saamay, Erglis, Andrejs, Gilis, Dainus, Nesterovics, Georgijs, Saripo, Vita, Meiere, Ruta, Skudrina, Gunda, Terauda, Elizabete, Jambart, Selim, Ayoub, Carine, Ghaleb, Youmna, Aliosaitiene, Urte, Kutkiene, Sandra, Abdul Kadir, Siti Hamimah Sheikh, Kasim, Noor Alicezah Mohd, Nor, Noor Shafina Mohd, Abdul Hamid, Hasidah, Abdul Razak, Suraya, Al-Khateeb, Alyaa, Abd Muid, Suhaila, Abdul Rahman, Thuhairah, Kasim, Sazzli Shahlan, Radzi, Ahmad Bakhtiar Md, Ibrahim, Khairul Shafiq, Rosli, Marshima Mohd, Razali, Rafezah, Chua, Yung An, Razman, Aimi Zafira, Nazli, Sukma Azureen, Aziz, Nazirul, Rosman, Azhari, Abdul Murad, NorAzian, Jalaludin, Mohd Amin, Abdul Latif, Ahmad Zubaidi, Azzopardi, C., Mehta, Roopa, Martagon, Alexandro J., Ramirez, Gabriela A. Galan, Villa, Neftali E Antonio, Vazquez, Arsenio Vargas, Elias-Lopez, Daniel, Retana, Gustavo Gonzalez, Rodriguez, Betsabel, Macías, Jose J. Ceballos, Zazueta, Alejandro Romero, Alvarado, Rocio Martinez, Portano, Julieta D. Morales, Lopez, Humberto Alvares, Sauque-Reyna, Leobardo, Herrera, Laura G. Gomez, Mendia, Luis E. Simental, Aguilar, Humberto Garcia, Cooremans, Elizabeth Ramirez, Aparicio, Berenice Peña, Zubieta, Victoria Mendoza, Gonzalez, Perla A. Carrillo, Ferreira-Hermosillo, Aldo, Portilla, Nacu Caracas, Dominguez, Guadalupe Jimenez, Garcia, Alinna Y. Ruiz, Cazares, Hector E. Arriaga, Gonzalez, Jesus R., Valencia, Carla V. Mendez, Padilla, Francisco G., Prado, Ramon Madriz, Ibarra, Manuel O. De los Rios, Villicaña, Ruy D. Arjona, Rivera, Karina J. Acevedo, Carrera, Ricardo Allende, Alvarez, Jose A., Martinez, Jose C. Amezcua, Bustillo, Manuel de los Reyes Barrera, Vargas, Gonzalo Carazo, Chacon, Roberto Contreras, Andrade, Mario H. Figueroa, Ortega, Ashanty Flores, Alcala, Hector Garcia, de Leon, Laura E. Garcia, Guzman, Berenice Garcia, Garcia, Jose J. Garduño, Cuellar, Juan C. Garnica, Cruz, Jose R. Gomez, Garcia, Anell Hernandez, Almada, Jesus R. Holguin, Herrera, Ursulo Juarez, Sobrevilla, Fabiola Lugo, Rodriguez, Eduardo Marquez, Sibaja, Cristina Martinez, Rodriguez, Alma B. Medrano, Oyervides, Jose C. Morales, Vazquez, Daniel I. Perez, Rodriguez, Eduardo A. Reyes, Osorio, Ma. Ludivina Robles, Saucedo, Juan Rosas, Tamayo, Margarita Torres, Talavera, Luis A. Valdez, Arroyo, Luis E. Vera, Carrillo, Eloy A. Zepeda, Stroes, Erik S, Defesche, J, Zuurbier, L, Reeskamp, L, Ibrahim, S, Roeters van Lennep, Jeanine, Wiegman, Albert, Isara, Alphonsus, Obaseki, Darlington E., Al-Waili, Khalid, Al-Zadjali, Fahad, Al-Zakwani, Ibrahim, Al-Kindi, Mohammed, Al-Mukhaini, Suad, Al-Barwani, Hamida, Rana, Asim, Shah, Lahore Saeed Ullah, Al-Nouri, Fahad, Starostecka, Ewa, Konopka, Agnieszka, Bielecka-Dabrowa, Agata, Lewek, Joanna, Sosnowska, Bozena, Gąsior, Mariusz, Dyrbuś, Krzysztof, Jóźwiak, Jacek, Pajkowski, Marcin, Romanowska-Kocejko, Marzena, Żarczyńska-Buchowiecka, Marta, Chmara, Magdalena, Wasąg, Bartosz, Stróżyk, Aneta, Michalska-Grzonkowska, Aleksandra, Medeiros, Ana Margarida, Alves, Ana Catarina, Silva, Francisco, Lobarinhas, Goreti, Palma, Isabel, de Moura, Jose Pereira, Rico, Miguel Toscano, Rato, Quitéria, Pais, Patrícia, Correia, Susana, Moldovan, Oana, Virtuoso, Maria João, Araujo, Francisco, Salgado, Jose Miguel, Colaço, Ines, Dumitrescu, Andreea, Lengher, Calin, Mosteoru, Svetlana, Meshkov, Alexey, Ershova, Alexandra, Rozhkova, Tatiana, Korneva, Victoria, Yu, Kuznetsova T., Zafiraki, Vitaliy, Voevoda, Mikhail, Gurevich, Victor, Duplyakov, Dmitry, Ragino, Yulia, Chubykina, Uliana, Shaposhnik, Igor, Alkaf, Fahmi, Khudari, Alia, Rwaili, Nawal, Al-Allaf, Faisal, Alghamdi, Mohammad, Batais, Mohammed A, Almigbal, Turky H, Kinsara, Abdulhalim, AlQudaimi, Ashraf Hammouda Ahmed, Awan, Zuhier, Elamin, Omer A, Altaradi, Hani, Popovic, Ljiljana, Singh, Sandra, Rasulic, Iva, Petakov, Ana, Lalic, Nebojsa M., Lam, Carolyn, Le, Tan Ju, Siang, Eric Lim Tien, Dissanayake, Sanjaya, I-Shing, Justin Tang, Shyong, Tai E, Jin, Terrance Chua Siang, Ting, Sharon Pek Li, Ming, Jeremy Hoe Kian, Drum, Chester Lee, Nastar, Fathima Ashna, Jia, Loh Wann, Ya, Natalie Koh Si, Jie, Marvin Chua Wei, Dalan, Rinkoo, Wei, Yong Quek, sian, Tiong Yee, Keong, Yeo Khung, Rong, Siau Kai, Jin, Darren Seah Ee, Ming, Ian Koh Jan, Chang, Tan Hong, Peng, Fabian Yap Kok, Vasanwala, Rashida Farhad, Raslova, Katarina, Balinth, Karin, Buganova, Ingrid, Fabryova, Lubomira, Kadurova, Michaela, Klabnik, Alexander, Kozárová, Miriam, Sirotiakova, Jana, Battelino, Tadej, Cevc, Matija, Debeljak, Marusa, Torkar, Ana Drole, Fras, Zlatko, Jug, Borut, Cugalj, Barbara Kern, Kovac, Jernej, Mlinaric, Matej, Sikonja, Jaka, Pilcher, Gillian Joan, Blom, D J, Wolmarans, K H, Brice, B C, Muñiz-Grijalvo, Ovidio, Díaz-Díaz, Jose Luis, de Isla, Leopoldo Pérez, Fuentes, Francisco, Badimon, Lina, Martin, François, Miserez, Eleonore B., Shipton, Janine L., Ganokroj, Poranee, Chattranukulchai, Pairoj, Jiamjarasrungsi, Wiroj, Thongtang, Nuntakorn, Krittayaphong, Rungroj, Vathesatogkit, Prin, Sriphrapradang, Chutintorn, Phimphilai, Mattabhorn, Leelawattana, Rattana, Anthanont, Pimjai, Suraamornkul, Swangjit, Deerochanawong, Chaicharn, Senthong, Vichai, Torpongpun, Artit, Suteerayongprasert, Panuwat, Pengpong, Nawarat, Sathavarodom, Nattapol, Sunanta, Usanee, Porntharukchareon, Thachanun, Kiatpanabhikul, Phatharaporn, Kaewkrasaesin, Chatchon, Kongkit, Jaruwan, Umphonsathien, Mongkontida, Akbulut, Mehmet, Alici, Gökhan, Bayram, Fahri, Can, Levent Hürkan, Celik, Ahmet, Ceyhan, Ceyhun, Coskun, Fatma Yilmaz, Demir, Mesut, Demircan, Sabri, Dogan, Volkan, Durakoglugil, Emre, Dural, İbrahim Etem, Gedikli, Omer, Hacioglu, Aysa, Ildizli, Muge, Kilic, Salih, Kirilmaz, Bahadir, Kutlu, Merih, Oguz, Aytekin, Ozdogan, Oner, Onrat, Ersel, Ozer, Savas, Sabuncu, Tevfik, Sahin, Tayfun, Sivri, Fatih, Sonmez, Alper, Temizhan, Ahmet, Topcu, Selim, Tokgozoglu, Lale, Tuncez, Abdullah, Vural, Mirac, Yenercag, Mustafa, Yesilbursa, Dilek, Yigit, Zerrin, Yildirim, Aytul Belgi, Yildirir, Aylin, Yilmaz, Mehmet Birhan, Atallah, Bassam, Traina, Mahmoud, Sabbour, Hani, Abdul Hay, Dana, Luqman, Neama, Elfatih, Abubaker, Abdulrasheed, Arshad, Manla, Yosef, Kwok, See, DellOca, Nicolas, Alieva, Rano B., Fozilov, Khurshid G., Hoshimov, Shavkat U., Nizamov, Ulugbek I., Kan, Liliya E., Kim, Andrey R., Abdullaeva, Guzal J., Abdullaev, Alisher A., Do, Doan Loi, Nguyen, Mai Ngoc Thi, Kim, Ngoc Thanh, Le, Thanh Tung, Le, Hong An, and Ray, Kausik K.

Published
2024
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21. Characterizing Morphometric and Nanomechanical Malignant Cell Features in a Rare Paediatric γδ T-acute Lymphoblastic Leukaemia: Insights from a Single Case Study Using Atomic Force Microscopy

Author

Konstantin Bachvarov, Velichka Strijkova, Borislava Antonova, Maya Jordanova, Yoan Dimitrov, and Svetla Todinova

Subjects
childhood t-cell acute lymphoblastic leukaemia, atomic force microscopy, t-lymphoblast, cell morphology, membrane roughness, young’s modulus, Biology (General), QH301-705.5
Abstract

The most common cancer in paediatric age is acute lymphoblastic leukaemia (ALL) which accounts for nearly a quarter of all cases of paediatric cancer. ALL cases are classified as B-cell or T-cell precursor ALL, based on their immunophenotypical features. Patients with T-cell ALL (T-ALL) comprise 10–15% of all newly diagnosed cases and are more prevalent in boys and in older age compared to the overall incidence peak age of ALL. In this case report, we present the morphometric and nanomechanical features of T-lymphoblasts derived from an 11-month-old infant with a rare subtype of γδ T-ALL with aggressive biological behavior. To investigate these features, we employed atomic force microscopy (AFM) and compared the blast cell deviations found in their nanostructure and elasticity to those of normal lymphocytes from a healthy child. The malignant T-lymphoblasts exhibited reduced roughness and Young’s modulus values. This single case analysis demonstrates the potential of the AFM method to provide additional information regarding the characteristics of malignant cells and suggests its potential as a complementary approach for distinguishing neoplastic cells from normal cells. The application of AFM could potentially facilitate the introduction of in vitro tests to determine the efficacy of anti-leukemic treatments.

Published
2023
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22. The GENESIS database and tools: A decade of discovery in Mendelian genomics

Author

Danzi, Matt C., Powell, Eric, Rebelo, Adriana P., Dohrn, Maike F., Beijer, Danique, Fazal, Sarah, Xu, Isaac R.L., Medina, Jessica, Chen, Sitong, Arcia de Jesus, Yeisha, Schatzman, Jacquelyn, Hershberger, Ray E., Saporta, Mario, Baets, Jonathan, Falk, Marni, Herrmann, David N., Scherer, Steven S., Reilly, Mary M., Cortese, Andrea, Marques, Wilson, Cornejo-Olivas, Mario R., Sanmaneechai, Oranee, Kennerson, Marina L., Jordanova, Albena, Silva, Thiago Y.T., Pedroso, Jose Luiz, Schierbaum, Luca, Ebrahimi-Fakhari, Darius, Peric, Stojan, Lee, Yi-Chung, Synofzik, Matthis, Tekin, Mustafa, Ravenscroft, Gianina, Shy, Mike, Basak, Nazli, Schule, Rebecca, and Zuchner, Stephan

Published
2024
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26. Alternative splicing expands the clinical spectrum of NDUFS6-related mitochondrial disorders

Author

Armirola-Ricaurte, Camila, Zonnekein, Noortje, Koutsis, Georgios, Amor-Barris, Silvia, Pelayo-Negro, Ana Lara, Atkinson, Derek, Efthymiou, Stephanie, Turchetti, Valentina, Dinopoulos, Argyris, Garcia, Antonio, Karakaya, Mert, Moris, German, Polat, Ayşe Ipek, Yiş, Uluç, Espinos, Carmen, Van de Vondel, Liedewei, De Vriendt, Els, Karadima, Georgia, Wirth, Brunhilde, Hanna, Michael, Houlden, Henry, Berciano, Jose, and Jordanova, Albena

Published
2024
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28. Tyrosyl-tRNA synthetase has a noncanonical function in actin bundling

Author

Ermanoska, Biljana, Asselbergh, Bob, Morant, Laura, Petrovic-Erfurth, Maria-Luise, Hosseinibarkooie, Seyyedmohsen, Leitão-Gonçalves, Ricardo, Almeida-Souza, Leonardo, Bervoets, Sven, Sun, Litao, Lee, LaTasha, Atkinson, Derek, Khanghahi, Akram, Tournev, Ivaylo, Callaerts, Patrick, Verstreken, Patrik, Yang, Xiang-Lei, Wirth, Brunhilde, Rodal, Avital A., Timmerman, Vincent, Goode, Bruce L., Godenschwege, Tanja A., and Jordanova, Albena

Published
2023
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30. Merging of bivariate compound Binomial processes with shocks

Author

Jordanova, Pavlina K. and Veleva, Evelina

Subjects
Mathematics - Probability
Abstract

The paper investigates a discrete time Binomial risk model with different types of polices and shock events may influence some of the claim sizes. It is shown that this model can be considered as a particular case of the classical compound Binomial model. As far as we work with parallel Binomial counting processes in infinite time, if we consider them as independent, the probability of the event they to have at least once simultaneous jumps would be equal to one. We overcome this problem by using thinning instead of convolution operation. The bivariate claim counting processes are expressed in two different ways. The characteristics of the total claim amount processes are derived. The risk reserve process and the probabilities of ruin are discussed. The deficit at ruin is thoroughly investigated when the initial capital is zero. Its mean, probability mass function and probability generating function are obtained. We show that although the probability generating function of the global maxima of the random walk is uniquely determined via its probability mass function and vice versa, any compound geometric distribution with non-negative summands has uncountably many stochastically equivalent compound geometric presentations. The probability to survive in much more general settings, than those, discussed here, for example in the Anderson risk model, has uncountably many Beekman's convolution series presentations., Comment: submitted

Published
2021
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31. Preliminary Data on Escherichia coli, Yersinia enterocolitica, and Other Bacteria, as Well as Absent African Swine Fever Virus in the Gut Microbiota of Wild Mice and Voles from Bulgaria

Author

Yana Ilieva, Maya Margaritova Zaharieva, Lyudmila Dimitrova, Mila D. Kaleva, Joanna Jordanova, Maya Dimitrova, Michaela Beltcheva, Iliana Aleksieva, Yordan Georgiev, Yordan Manasiev, and Hristo Najdenski

Subjects
wild rodents, small mammals, Escherichia coli, Yersinia enterocolitica, Bacillus thuringiensis, Hafnia alvei, Microbiology, QR1-502
Abstract

Small mammals are bioindicator organisms, and, through their gut microbiota (GM), could be carriers of pathogens and resistant bacteria. Also, wild GM composition has been suggested to have large implications for conservation efforts. Seventeen bacterial species were obtained from intestinal samples of Bulgarian yellow-necked mice (Apodemus flavicollis) and bank voles (Myodes glareolus) via classic microbiological cultivation and biochemical identification. Twelve Gram-negative—Escherichia coli, Yersinia enterocolitica, Yersinia kristensenii, Hafnia alvei, Serratia liquefaciens, Serratia marcescens, Serratia proteamaculans, Pseudescherichia vulneris, Klebsiella pneumoniae ssp. ozaenae, Enterobacter cloacea, Pantoea agglomerans, Pseudomonas fluorescens group—and five Gram-positive bacteria, Enterococcus faecium, Enterococcus faecalis, Enterococcus hirae, Bacillus thuringiensis, and Lysinibacillus sphaericus, were discovered. Enterobacteriaceae was the most abundant family. The isolates belonged to one of the major reported taxa in rodents, Firmicutes (the Gram-positive species) and to the less abundant, but still among the first, phyla, Proteobacteria (the Gram-negative strains). We did not find any members of the other major phylum, Bacteroidetes, likely due to lack of metagenomic techniques. E. coli and Y. enterocolitica were confirmed with polymerase chain reaction. Almost all strains had pathogenic potential, but the good condition of the test animals suggests their commensal role. The Y. enterocolitica strains did not have the ail pathogenicity gene. There was high prevalence of multi-drug resistance (MDR), but for the expected species with high level of intrinsic resistance, such as the enterococci and S. marcescens. E. coli and some other species had very low antimicrobial resistance (AMR), in line with other studies of wild rodents. Many of the strains had biotechnological potential; e.g., B. thuringiensis is the most used biological insecticide, with its proteins incorporated into the Bt genetically modified maize. The GM of the tested wild mice and voles from Bulgaria proved to be a source of bacterial diversity; many of the strains were promising in terms of biotechnology, and, in addition, the samples did not contain the African swine fever virus.

Published
2023
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32. Determination of the expression of bone morphogen protein 15 and its receptors in laying hens’ ovary

Author

Desislava Vasileva Abadjieva and Svetlana Jordanova Grigorova

Subjects
laying hens, bone morphogenetic protein 15, gene expression, Veterinary medicine, SF600-1100
Abstract

The objective of the current research was to determine expression, function and regulation of bone morphogenetic protein 15 (BMP15) during follicular development in laying hens. A trial was conducted with 40 layers from Lohman Klassik Brown breed (40 weeks old). At the end of the study fifteen layers were humanely killed and their ovaries were then dissected. Ribonucleic acid (RNA) expression of BMP15 was analyzed in the ooplasm and in granulosa cells. It was significantly higher in the ooplasm (p9 mm follicles. The expression for bone morphogenetic protein 15 receptors (BMPR1B and BMPR2) in the granulosa cells was in significant positive correlation with the follicle size (p

Published
2023
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35. New constraints on the Middle-Late Pleistocene Campi Flegrei explosive activity and Mediterranean tephrostratigraphy (∼160 ka and 110–90 ka)

Author

Fernandez, Giada, Giaccio, Biagio, Costa, Antonio, Monaco, Lorenzo, Nomade, Sébastien, Albert, Paul G., Pereira, Alison, Flynn, Molly, Leicher, Niklas, Lucchi, Federico, Petrosino, Paola, Palladino, Danilo M., Milia, Alfonsa, Insinga, Donatella Domenica, Wulf, Sabine, Kearney, Rebecca, Veres, Daniel, Jordanova, Diana, Putignano, Maria Luisa, Isaia, Roberto, and Sottili, Gianluca

Published
2024
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36. Identification and Characterization of Novel Founder Mutations in NDRG1: Refining the Genetic Landscape of Charcot–Marie–Tooth Disease Type 4D in Bulgaria

Author

Derek Atkinson, Teodora Chamova, Ayse Candayan, Kristina Kastreva, Ognian Asenov, Ivan Litvinenko, Alejandro Estrada-Cuzcano, Els De Vriendt, Georgi Kukushev, Ivailo Tournev, and Albena Jordanova

Subjects
NDRG1, Charcot–Marie–Tooth neuropathy type 4D, demyelinating neuropathy, founder mutation, non-Roma ethnicity, Biology (General), QH301-705.5, Chemistry, QD1-999
Abstract

Charcot–Marie–Tooth neuropathy type 4D (CMT4D) is a rare genetic disorder of the peripheral nervous system caused by biallelic mutations in the N-Myc Downstream Regulated 1 gene (NDRG1). Patients present with an early onset demyelinating peripheral neuropathy causing severe distal muscle weakness and sensory loss, leading to loss of ambulation and progressive sensorineural hearing loss. The disorder was initially described in the Roma community due to a common founder mutation, and only a handful of disease-causing variants have been described in this gene so far. Here, we present genetic and clinical findings from a large Bulgarian cohort of demyelinating CMT patients harboring recurrent and novel variants in the NDRG1 gene. Notably, two splice-site variants are exclusive to Bulgarian Muslims and reside in ancestral haplotypes, suggesting a founder effect. Functional characterization of these novel variants implicates a loss-of-function mechanism due to shorter gene products. Our findings contribute to a deeper understanding of the genetic and clinical heterogeneity of CMT4D and highlight novel founder mutations in the ethnic minority of Bulgarian Muslims.

Published
2024
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39. Overview, progress and next steps for our understanding of the near-earth space radiation and plasma environment: Science and applications

Author

Zheng, Yihua, Jun, Insoo, Tu, Weichao, Shprits, Yuri Y., Kim, Wousik, Matthiä, Daniel, Meier, Matthias M., Kent Tobiska, W., Miyoshi, Yoshizumi, Jordanova, Vania K., Ganushkina, Natalia Y., Tenishev, Valeriy, O’Brien, T.P., Brunet, Antoine, Maget, Vincent, Guo, Jingnan, Wang, Dedong, Horne, Richard B., Glauert, Sarah, Haas, Bernhard, and Drozdov, Alexander Y.

Published
2024
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41. Proinflammatory activity of VEGF-targeted treatment through reversal of tumor endothelial cell anergy

Author

Nowak-Sliwinska, Patrycja, van Beijnum, Judy R., Griffioen, Christian J., Huinen, Zowi R., Sopesens, Nadine Grima, Schulz, Ralph, Jenkins, Samir V., Dings, Ruud P. M., Groenendijk, Floris H., Huijbers, Elisabeth J. M., Thijssen, Victor L. J. L., Jonasch, Eric, Vyth-Dreese, Florry A., Jordanova, Ekaterina S., Bex, Axel, Bernards, René, de Gruijl, Tanja D., and Griffioen, Arjan W.

Published
2023
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42. Two Brothers from Macedonia with Gitelman Syndrome

Author

Janchevska A, Tasic V, Jordanova O, Gucev Z, Jenkins L, Jovanovska N, Plaseska-Karanfilska D, Ashton E, and Bockenhauer D

Subjects
gitelman syndrome, hypokalemia, hypomagnesemia, hypocalciuria, slc12a3, Genetics, QH426-470
Abstract

Gitelman syndrome (GS) is a rare renal tubulopathy with an autosomal recessive mode of inheritance, caused by biallelic pathogenic variants in the SLC12A3 gene. The clinical features may overlap with other disorders, such as Bartter syndrome type 3, HNF1B nephropathy or even mitochondrial disease, but can be distinguished by molecular genetic analysis.

Published
2023
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43. Iron oxide nanoparticles as positive T1 contrast agents for low-field magnetic resonance imaging at 64 mT

Author

Samuel D. Oberdick, Kalina V. Jordanova, John T. Lundstrom, Giacomo Parigi, Megan E. Poorman, Gary Zabow, and Kathryn E. Keenan

Subjects
Medicine, Science
Abstract

Abstract We have investigated the efficacy of superparamagnetic iron oxide nanoparticles (SPIONs) as positive T1 contrast agents for low-field magnetic resonance imaging (MRI) at 64 millitesla (mT). Iron oxide-based agents, such as the FDA-approved ferumoxytol, were measured using a variety of techniques to evaluate T1 contrast at 64 mT. Additionally, we characterized monodispersed carboxylic acid-coated SPIONs with a range of diameters (4.9–15.7 nm) in order to understand size-dependent properties of T1 contrast at low-field. MRI contrast properties were measured using 64 mT MRI, magnetometry, and nuclear magnetic resonance dispersion (NMRD). We also measured MRI contrast at 3 T to provide comparison to a standard clinical field strength. SPIONs have the capacity to perform well as T1 contrast agents at 64 mT, with measured longitudinal relaxivity (r1) values of up to 67 L mmol−1 s−1, more than an order of magnitude higher than corresponding r1 values at 3 T. The particles exhibit size-dependent longitudinal relaxivities and outperform a commercial Gd-based agent (gadobenate dimeglumine) by more than eight-fold at physiological temperatures. Additionally, we characterize the ratio of transverse to longitudinal relaxivity, r2/r1 and find that it is ~ 1 for the SPION based agents at 64 mT, indicating a favorable balance of relaxivities for T1-weighted contrast imaging. We also correlate the magnetic and structural properties of the particles with models of nanoparticle relaxivity to understand generation of T1 contrast. These experiments show that SPIONs, at low fields being targeted for point-of-care low-field MRI systems, have a unique combination of magnetic and structural properties that produce large T1 relaxivities.

Published
2023
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44. Distribution sensitive estimators of the index of regular variation based on ratios of order statistics

Author

Jordanova, Pavlina K. and k, Milan Stehlí

Subjects
Mathematics - Statistics Theory, 62F10
Abstract

Ratios of central order statistics seem to be very useful for estimating the tail of the distributions and therefore, quantiles outside the range of the data. In 1995 Isabel Fraga Alves investigated the rate of convergence of three semi-parametric estimators of the parameter of the tail index in case when the cumulative distribution function of the observed random variable belongs to the max-domain of attraction of a fixed Generalized Extreme Value Distribution. They are based on ratios of specific linear transformations of two extreme order statistics. In 2019 we considered Pareto case and found two very simple and unbiased estimators of the index of regular variation. Then, using the central order statistics we showed that these estimators have many good properties. Then, we observed that although the assumptions are different, one of them is equivalent to one of Alves's estimators. Using central order statistics we proved unbiasedness, asymptotic consistency, asymptotic normality and asymptotic efficiency. Here we use again central order statistics and a parametric approach and obtain distribution sensitive estimators of the index of regular variation in some particular cases. Then, we find conditions which guarantee that these estimators are unbiased, consistent and asymptotically normal. The results are depicted via simulation study.

Published
2020
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45. Assimilation of distributed ocean wave sensors

Author

Smit, Pieter B., Houghton, Isabel A., Jordanova, Kalina, Portwood, Thomas, Shapiro, Evan, Clark, David, Sosa, Michael, and Janssen, Tim T.

Subjects
Physics - Atmospheric and Oceanic Physics, Physics - Data Analysis, Statistics and Probability
Abstract

In-situ ocean wave observations are critical to improve model skill and validate remote sensing wave measurements. Historically, such observations are extremely sparse due to the large costs and complexity of traditional wave buoys and sensors. In this work, we present a recently deployed network of free-drifting satellite-connected surface weather buoys that provide long-dwell coverage of surface weather in the northern Pacific Ocean basin. To evaluate the leading-order improvements to model forecast skill using this distributed sensor network, we implement a widely-used data assimilation technique and compare forecast skill to the same model without data assimilation. Even with a basic assimilation strategy as used here, we find remarkable improvements to forecast accuracy from the incorporation of wave buoy observations, with a 27% reduction in root-mean-square error in significant waveheights overall. For an extreme event, where forecast accuracy is particularly relevant, we observe considerable improvements in both arrival time and magnitude of the swell on the order of 6 hours and 1 m, respectively. Our results show that distributed ocean networks can meaningfully improve model skill, at extremely low cost. Refinements to the assimilation strategy are straightforward to achieve and will result in immediate further modelling gains., Comment: 36 pages, 7 figures

Published
2020

50. Cerebellar presence of immune cells in patients with neuro-coeliac disease

Author

Maxine D. Rouvroye, Hetty J. Bontkes, John G. J. M. Bol, Birgit Lissenberg-Witte, Valerie Byrnes, Fadel Bennani, Ekaterina S. Jordanova, Micha M. M. Wilhelmus, Chris J. Mulder, Paul van der Valk, Annemieke J. M. Rozemuller, Gerd Bouma, and Anne-Marie Van Dam

Subjects
Gluten, Coeliac disease, Neurological disorders, Ataxia, Encephalopathy, Lymphocyte, Neurology. Diseases of the nervous system, RC346-429
Abstract

Abstract Although various neurodegenerative disorders have been associated with coeliac disease (CD), the underlying neuropathological link between these brain and gut diseases remains unclear. We postulated that the neuronal damage sporadically observed in CD patients is immune-mediated. Our aim was to determine if the loss of neurons, especially Purkinje cells, coincides with microglia activation and T- and B-cell infiltration in the cerebellum of patients with CD and a concomitant idiopathic neurological disease affecting the cerebellum (NeuroCD). Post-mortem cerebellar tissue was collected of validated NeuroCD cases. Gender- and age-matched genetic spinocerebellar ataxia (SCA) controls and non-neurological controls (NNC) were selected based on clinical reports and pathological findings. Cerebellar tissue of seventeen patients was included (6 NeuroCD, 5 SCA, 6 NNC). In SCA cases we found that the Purkinje cell layer was 58.6% reduced in comparison with NNC. In NeuroCD cases this reduction was even more prominent with a median reduction of 81.3% compared to NNC. Marked increased numbers of both CD3+ and CD8+ cells were observed in the NeuroCD but not in SCA patients. This coincided with significantly more microglial reactivity in NeuroCD patients. These findings demonstrate that the massive loss of Purkinje cells in the cerebellum of neuro CD patients is accompanied by local innate and T-cell mediated immune responses.

Published
2023
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