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Article ; Online: Automated imaging coupled with AI-powered analysis accelerates the assessment of plant resistance to Tetranychus urticae.

Złotkowska, Ewelina / Wlazło, Anna / Kiełkiewicz, Małgorzata / Misztal, Krzysztof / Dziosa, Paulina / Soja, Krzysztof / Barczak-Brzyżek, Anna / Filipecki, Marcin

Scientific reports

2024 Volume 14, Issue 1, Page(s) 8020

Abstract: The two-spotted spider mite (TSSM), Tetranychus urticae, is among the most destructive piercing-sucking herbivores, infesting more than 1100 plant species, including numerous greenhouse and open-field crops of significant economic importance. Its ... ...

Abstract	The two-spotted spider mite (TSSM), Tetranychus urticae, is among the most destructive piercing-sucking herbivores, infesting more than 1100 plant species, including numerous greenhouse and open-field crops of significant economic importance. Its prolific fecundity and short life cycle contribute to the development of resistance to pesticides. However, effective resistance loci in plants are still unknown. To advance research on plant-mite interactions and identify genes contributing to plant immunity against TSSM, efficient methods are required to screen large, genetically diverse populations. In this study, we propose an analytical pipeline utilizing high-resolution imaging of infested leaves and an artificial intelligence-based computer program, MITESPOTTER, for the precise analysis of plant susceptibility. Our system accurately identifies and quantifies eggs, feces and damaged areas on leaves without expert intervention. Evaluation of 14 TSSM-infested Arabidopsis thaliana ecotypes originating from diverse global locations revealed significant variations in symptom quantity and distribution across leaf surfaces. This analytical pipeline can be adapted to various pest and host species, facilitating diverse experiments with large specimen numbers, including screening mutagenized plant populations or phenotyping polymorphic plant populations for genetic association studies. We anticipate that such methods will expedite the identification of loci crucial for breeding TSSM-resistant plants.
MeSH term(s)	Animals ; Tetranychidae/genetics ; Artificial Intelligence ; Plant Breeding ; Plants ; Arabidopsis
Language	English
Publishing date	2024-04-05
Publishing country	England
Document type	Journal Article
ZDB-ID	2615211-3
ISSN	2045-2322 ; 2045-2322
ISSN (online)	2045-2322
ISSN	2045-2322
DOI	10.1038/s41598-024-58249-7
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: The importance of standardisation - COVID-19 CT & Radiograph Image Data Stock for deep learning purpose.

Misztal, Krzysztof / Pocha, Agnieszka / Durak-Kozica, Martyna / Wątor, Michał / Kubica-Misztal, Aleksandra / Hartel, Marcin

Computers in biology and medicine

2020 Volume 127, Page(s) 104092

Abstract: With the number of affected individuals still growing world-wide, the research on COVID-19 is continuously expanding. The deep learning community concentrates their efforts on exploring if neural networks can potentially support the diagnosis using CT ... ...

Abstract	With the number of affected individuals still growing world-wide, the research on COVID-19 is continuously expanding. The deep learning community concentrates their efforts on exploring if neural networks can potentially support the diagnosis using CT and radiograph images of patients' lungs. The two most popular publicly available datasets for COVID-19 classification are COVID-CT and COVID-19 Image Data Collection. In this work, we propose a new dataset which we call COVID-19 CT & Radiograph Image Data Stock. It contains both CT and radiograph samples of COVID-19 lung findings and combines them with additional data to ensure a sufficient number of diverse COVID-19-negative samples. Moreover, it is supplemented with a carefully defined split. The aim of COVID-19 CT & Radiograph Image Data Stock is to create a public pool of CT and radiograph images of lungs to increase the efficiency of distinguishing COVID-19 disease from other types of pneumonia and from healthy chest. We hope that the creation of this dataset would allow standardisation of the approach taken for training deep neural networks for COVID-19 classification and eventually for building more reliable models.
MeSH term(s)	COVID-19/diagnostic imaging ; COVID-19/virology ; Deep Learning ; Humans ; Lung/diagnostic imaging ; Radiographic Image Interpretation, Computer-Assisted/methods ; SARS-CoV-2/isolation & purification ; Tomography, X-Ray Computed/standards
Keywords	covid19
Language	English
Publishing date	2020-10-28
Publishing country	United States
Document type	Journal Article
ZDB-ID	127557-4
ISSN	1879-0534 ; 0010-4825
ISSN (online)	1879-0534
ISSN	0010-4825
DOI	10.1016/j.compbiomed.2020.104092
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Book ; Online: SLOVA

Wójcik, Bartosz / Grela, Jacek / Śmieja, Marek / Misztal, Krzysztof / Tabor, Jacek

Uncertainty Estimation Using Single Label One-Vs-All Classifier

2022

Abstract: Deep neural networks present impressive performance, yet they cannot reliably estimate their predictive confidence, limiting their applicability in high-risk domains. We show that applying a multi-label one-vs-all loss reveals classification ambiguity ... ...

Abstract	Deep neural networks present impressive performance, yet they cannot reliably estimate their predictive confidence, limiting their applicability in high-risk domains. We show that applying a multi-label one-vs-all loss reveals classification ambiguity and reduces model overconfidence. The introduced SLOVA (Single Label One-Vs-All) model redefines typical one-vs-all predictive probabilities to a single label situation, where only one class is the correct answer. The proposed classifier is confident only if a single class has a high probability and other probabilities are negligible. Unlike the typical softmax function, SLOVA naturally detects out-of-distribution samples if the probabilities of all other classes are small. The model is additionally fine-tuned with exponential calibration, which allows us to precisely align the confidence score with model accuracy. We verify our approach on three tasks. First, we demonstrate that SLOVA is competitive with the state-of-the-art on in-distribution calibration. Second, the performance of SLOVA is robust under dataset shifts. Finally, our approach performs extremely well in the detection of out-of-distribution samples. Consequently, SLOVA is a tool that can be used in various applications where uncertainty modeling is required.
Keywords	Computer Science - Machine Learning
Subject code	519
Publishing date	2022-06-28
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Finite-element lattice Boltzmann simulations of contact line dynamics.

Matin, Rastin / Krzysztof Misztal, Marek / Hernández-García, Anier / Mathiesen, Joachim

Physical review. E

2018 Volume 97, Issue 1-1, Page(s) 13307

Abstract: The lattice Boltzmann method has become one of the standard techniques for simulating a wide range of fluid flows. However, the intrinsic coupling of momentum and space discretization restricts the traditional lattice Boltzmann method to regular lattices. ...

Abstract	The lattice Boltzmann method has become one of the standard techniques for simulating a wide range of fluid flows. However, the intrinsic coupling of momentum and space discretization restricts the traditional lattice Boltzmann method to regular lattices. Alternative off-lattice Boltzmann schemes exist for both single- and multiphase flows that decouple the velocity discretization from the underlying spatial grid. The current study extends the applicability of these off-lattice methods by introducing a finite element formulation that enables simulating contact line dynamics for partially wetting fluids. This work exemplifies the implementation of the scheme and furthermore presents benchmark experiments that show the scheme reduces spurious currents at the liquid-vapor interface by at least two orders of magnitude compared to a nodal implementation and allows for predicting the equilibrium states accurately in the range of moderate contact angles.
Language	English
Publishing date	2018-01
Publishing country	United States
Document type	Journal Article
ZDB-ID	2844562-4
ISSN	2470-0053 ; 2470-0045
ISSN (online)	2470-0053
ISSN	2470-0045
DOI	10.1103/PhysRevE.97.013307
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Article ; Online: The importance of standardisation – COVID-19 CT & Radiograph Image Data Stock for deep learning purpose

Misztal, Krzysztof / Pocha, Agnieszka / Durak-Kozica, Martyna / Wątor, Michał / Kubica-Misztal, Aleksandra / Hartel, Marcin

Computers in Biology and Medicine

2020 Volume 127, Page(s) 104092

Keywords	Health Informatics ; Computer Science Applications ; covid19
Language	English
Publisher	Elsevier BV
Publishing country	us
Document type	Article ; Online
ZDB-ID	127557-4
ISSN	1879-0534 ; 0010-4825
ISSN (online)	1879-0534
ISSN	0010-4825
DOI	10.1016/j.compbiomed.2020.104092
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article: The importance of standardisation - COVID-19 CT & Radiograph Image Data Stock for deep learning purpose

Misztal, Krzysztof / Pocha, Agnieszka / Durak-Kozica, Martyna / Wator, Michal / Kubica-Misztal, Aleksandra / Hartel, Marcin

Comput Biol Med

Abstract	With the number of affected individuals still growing world-wide, the research on COVID-19 is continuously expanding. The deep learning community concentrates their efforts on exploring if neural networks can potentially support the diagnosis using CT and radiograph images of patients' lungs. The two most popular publicly available datasets for COVID-19 classification are COVID-CT and COVID-19 Image Data Collection. In this work, we propose a new dataset which we call COVID-19 CT & Radiograph Image Data Stock. It contains both CT and radiograph samples of COVID-19 lung findings and combines them with additional data to ensure a sufficient number of diverse COVID-19-negative samples. Moreover, it is supplemented with a carefully defined split. The aim of COVID-19 CT & Radiograph Image Data Stock is to create a public pool of CT and radiograph images of lungs to increase the efficiency of distinguishing COVID-19 disease from other types of pneumonia and from healthy chest. We hope that the creation of this dataset would allow standardisation of the approach taken for training deep neural networks for COVID-19 classification and eventually for building more reliable models.
Keywords	covid19
Publisher	WHO
Document type	Article
Note	WHO #Covidence: #915394
Database	COVID19

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Article ; Online: Large extracellular vesicles do not mitigate the harmful effect of hyperglycemia on endothelial cell mobility.

Drożdż, Anna / Kołodziej, Tomasz / Wróbel, Sonia / Misztal, Krzysztof / Targosz-Korecka, Marta / Drab, Marek / Jach, Robert / Rząca, Carina / Surman, Magdalena / Przybyło, Małgorzata / Rajfur, Zenon / Stępień, Ewa Ł

European journal of cell biology

2022 Volume 101, Issue 4, Page(s) 151266

Abstract: Extracellular vesicles, especially the larger fraction (LEVs - large extracellular vesicles), are believed to be an important means of intercellular communication. Earlier studies on LEVs have shown their healing properties, especially in the vascular ... ...

Abstract	Extracellular vesicles, especially the larger fraction (LEVs - large extracellular vesicles), are believed to be an important means of intercellular communication. Earlier studies on LEVs have shown their healing properties, especially in the vascular cells of diabetic patients. Uptake of LEVs by endothelial cells and internalization of their cargo have also been demonstrated. Endothelial cells change their properties under hyperglycemic conditions (HGC), which reduces their activity and is the cause of endothelial dysfunction. The aim of our study was to investigate how human umbilical vein endothelial cells (HUVECs) change their biological properties: shape, mobility, cell surface stiffness, as well as describe the activation of metabolic pathways after exposure to the harmful effects of HGC and the administration of LEVs released by endothelial cells. We obtained LEVs from HUVEC cultures in HGC and normoglycemia (NGC) using the filtration and ultracentrifugation methods. We assessed the size of LEVs and the presence of biomarkers such as phosphatidylserine, CD63, beta-actin and HSP70. We analyzed the LEVs uptake efficiency by HUVECs, HUVEC shape, actin cytoskeleton remodeling, surface stiffness and finally gene expression by mRNA analysis. Under HGC conditions, HUVECs were larger and had a stiffened surface and a strengthened actin cortex compared to cells under NGC condition. HGC also altered the activation of metabolic pathways, especially those related to intracellular transport, metabolism, and organization of cellular components. The most interesting observation in our study is that LEVs did not restore cell motility disturbed by HGC. Although, LEVs were not able to reverse this deleterious effect of HGC, they activated transcription of genes involved in protein synthesis and vesicle trafficking in HUVECs.
Language	English
Publishing date	2022-08-04
Publishing country	Germany
Document type	Journal Article
ZDB-ID	391967-5
ISSN	1618-1298 ; 0070-2463 ; 0171-9335
ISSN (online)	1618-1298
ISSN	0070-2463 ; 0171-9335
DOI	10.1016/j.ejcb.2022.151266
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Article: How Medical Studies in Poland Prepare Future Healthcare Managers for Crises and Disasters: Results of a Pilot Study.

Misztal-Okońska, Patrycja / Goniewicz, Krzysztof / Hertelendy, Attila J / Khorram-Manesh, Amir / Al-Wathinani, Ahmed / Alhazmi, Riyadh A / Goniewicz, Mariusz

Healthcare (Basel, Switzerland)

2020 Volume 8, Issue 3

Abstract: In the event of a crisis, rapid and effective assistance for victims is essential, and in many cases, medical assistance is required. To manage the situation efficiently, it is necessary to have a proactive management system in place that ensures ... ...

Abstract	In the event of a crisis, rapid and effective assistance for victims is essential, and in many cases, medical assistance is required. To manage the situation efficiently, it is necessary to have a proactive management system in place that ensures professional assistance to victims and the safety of medical personnel. We evaluated the perceptions of students and graduates in public health studies at the Medical University of Lublin, Poland, concerning their preparation and management skills for crises such as the COVID-19 pandemic. This pilot study was conducted in March 2020; we employed an online survey with an anonymous questionnaire that was addressed to students and graduates with an educational focus in healthcare organization and management. The study involved 55 people, including 14 men and 41 women. Among the respondents, 41.8% currently worked in a healthcare facility and only 21.7% of them had participated in training related to preparation for emergencies and disasters in their current workplace. The respondents rated their workplaces' preparedness for the COVID-19 pandemic at four points. A significant number of respondents stated that if they had to manage a public health emergency, they would not be able to manage the situation correctly and not be able to predict its development. Managers of healthcare organizations should have the knowledge and skills to manage crises. It would be advisable for them to have been formally educated in public health or healthcare administration. In every healthcare facility, it is essential that training and practice of performing medical procedures in full personal protective equipment (PPE) be provided. Healthcare facilities must implement regular training combined with practical live scenario exercises to prepare for future crises.
Keywords	covid19
Language	English
Publishing date	2020-07-09
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2721009-1
ISSN	2227-9032
ISSN	2227-9032
DOI	10.3390/healthcare8030202
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Article ; Online: Evacuation from Healthcare Facilities in Poland: Legal Preparedness and Preparation.

Goniewicz, Krzysztof / Misztal-Okońska, Patrycja / Pawłowski, Witold / Burkle, Frederick M / Czerski, Robert / Hertelendy, Attila J / Goniewicz, Mariusz

International journal of environmental research and public health

2020 Volume 17, Issue 5

Abstract: Medical facilities, while providing both essential and demanding health care to society's most vulnerable populations, also belong to the most demanding category of risk to human life if and when a crisis event occurs within its walls. The development of ...

Abstract	Medical facilities, while providing both essential and demanding health care to society's most vulnerable populations, also belong to the most demanding category of risk to human life if and when a crisis event occurs within its walls. The development of a safe evacuation plan for these facilities is extremely complicated, as the evacuation of medical facilities is much more complex than for other critical infrastructure. In this category, the evacuated patients constitute a specific risk group requiring specialized medical care. Hospitalized persons may be dependent on life-saving measures, are unconscious or immobile, are significantly restricted in movement or mentally unbalanced, being dependent on the continued assistance of trained third parties. Additionally, the medical transport of evacuated patients becomes more difficult due to the limited capacity of ambulances and available health care facilities to transport them to, which are increasingly limited due to their overcrowded census. The study aimed to analyze the requirements which are placed on hospitals in Poland to ensure the safety of patients in case of an evacuation. The research method used in the paper was retrospective analysis and evaluation of the media and literature. We have found, that Polish law imposes an obligation on the administrator of a medical facility to ensure the safety of both patients and employees. The regulations cover issues of technical conditions to be met by buildings and their location, prevention, and fire protection requirements, and the determination of which staff is responsible for the evacuation. However, available documents fail to describe what the hospital evacuation process itself should entail under emergency evacuation. Taking into account the complexity of the hospital evacuation process, health care facilities should have a well-developed plan of action that must be implemented at least once a year in the form of facility-wide training. Evacuation drills should not be avoided. Only trained procedures offer the possibility of later analysis to identify and eliminate errors and provide the opportunity to acquire skill sets and habits which promote the behaviors expected in real-life emergencies.
MeSH term(s)	Civil Defense ; Emergencies ; Fires ; Health Facilities ; Humans ; Poland ; Retrospective Studies
Language	English
Publishing date	2020-03-09
Publishing country	Switzerland
Document type	Journal Article
ISSN	1660-4601
ISSN (online)	1660-4601
DOI	10.3390/ijerph17051779
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Article ; Online: Objective and Subjective Stress Parameters in Response to High and Low-Fidelity Simulation Activities.

Czekirda, Marta / Misztal-Okońska, Patrycja / Włoszczak-Szubzda, Anna / Goniewicz, Mariusz / Cybulski, Mateusz / Kowalczuk, Krystyna / Jaszyna, Noemi / Pyć, Maria / Gnat, Mariusz / Girzelska, Joanna / Guz, Ewa / Sutryk, Mariusz / Tuszyńska-Bogucka, Wioletta / Goniewicz, Krzysztof / Al-Wathinani, Ahmed M / Khorram-Manesh, Amir

International journal of environmental research and public health

2022 Volume 19, Issue 5

Abstract: Nursing graduates are required to have both excellent theoretical and practical skills that should be used during stressful emergency interventions. Since the received knowledge should be practiced to gain skills and trained to achieve competences, ... ...

Abstract	Nursing graduates are required to have both excellent theoretical and practical skills that should be used during stressful emergency interventions. Since the received knowledge should be practiced to gain skills and trained to achieve competences, simulation exercises can be beneficial to even reduce the stress that each individual may face during emergency management of patients. A total of 146 first-year nursing students participated in the study, including 124 women and 22 men aged between 19 and 50 years, with a mean age of 32 years. The objective method estimated psychophysiological parameters (serum cortisol). Objective and subjective methods were used. The subjective method assessed stress experienced by students based on the standardized Stress Appraisal Questionnaire Version B for dispositional assessment. The study was conducted in the Monoprofile Medical Simulation Centre at the University of Economics and Innovation in Lublin, Poland and was approved by the University Research Ethics Committee. Both participants under and over 25 years of age showed increased levels of stress after low and high-fidelity simulations, with statistically significantly higher stress levels found for the low fidelity method. Low-fidelity simulation methods generated a greater increase in cortisol levels, indicating a higher stress level than the high-fidelity methods. The analysis of the scores obtained in the Stress Appraisal Questionnaire (KOS-B) showed that higher cortisol levels after the low-fidelity simulation reduced the subjective perception of a threat, while higher cortisol levels before the high-fidelity simulation promoted higher intellectual activity among the students. Levels of stress in the education of nursing students using low and high-fidelity methods can limit the sense of threat and activate professional task performance. The use of low and high-fidelity simulation does not generate destructive stress levels.
MeSH term(s)	Adult ; Clinical Competence ; Female ; Humans ; Hydrocortisone ; Knowledge ; Male ; Middle Aged ; Students, Nursing ; Surveys and Questionnaires ; Young Adult
Chemical Substances	Hydrocortisone (WI4X0X7BPJ)
Language	English
Publishing date	2022-03-03
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2175195-X
ISSN	1660-4601 ; 1661-7827
ISSN (online)	1660-4601
ISSN	1661-7827
DOI	10.3390/ijerph19052980
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