Catalogue Search | MBRL
Are you sure you want to remove the book from the shelf?
{{itemTitle}}
2,703
result(s) for
"Klein, Martin"
Sort by:
Selected Biomarkers of Depression: What Are the Effects of Cytokines and Inflammation?
Depression is one of the leading mental illnesses worldwide and lowers the quality of life of many. According to WHO, about 5% of the worldwide population suffers from depression. Newer studies report a staggering global prevalence of 27.6%, and it is rising. Professionally, depression belonging to affective disorders is a psychiatric illness, and the category of major depressive disorder (MDD) comprises various diagnoses related to persistent and disruptive mood disorders. Due to this fact, it is imperative to find a way to assess depression quantitatively using a specific biomarker or a panel of biomarkers that would be able to reflect the patients’ state and the effects of therapy. Cytokines, hormones, oxidative stress markers, and neuropeptides are studied in association with depression. The latest research into inflammatory cytokines shows that their relationship with the etiology of depression is causative. There are stronger cytokine reactions to pathogens and stressors in depression. If combined with other predisposing factors, responses lead to prolonged inflammatory processes, prolonged dysregulation of various axes, stress, pain, mood changes, anxiety, and depression. This review focuses on the most recent data on cytokines as markers of depression concerning their roles in its pathogenesis, their possible use in diagnosis and management, their different levels in bodily fluids, and their similarities in animal studies. However, cytokines are not isolated from the pathophysiologic mechanisms of depression or other psychiatric disorders. Their effects are only a part of the whole pathway.
Journal Article
Plato and a platypus walk into a bar ... : understanding philosophy through jokes
Teaches the principles and concepts of philosophy through one-liner jokes, vaudeville humor, cartoons, and limericks, in an irreverent introduction to the great philosophers and philosophical traditions, from Existentialism to Logic.
Effects of the COVID-19 pandemic on mental health, anxiety, and depression
Background
The COVID-19 pandemic affected everyone around the globe. Depending on the country, there have been different restrictive epidemiologic measures and also different long-term repercussions. Morbidity and mortality of COVID-19 affected the mental state of every human being. However, social separation and isolation due to the restrictive measures considerably increased this impact. According to the World Health Organization (WHO), anxiety and depression prevalence increased by 25% globally. In this study, we aimed to examine the lasting effects of the COVID-19 pandemic on the general population.
Methods
A cross-sectional study using an anonymous online-based 45-question online survey was conducted at Comenius University in Bratislava. The questionnaire comprised five general questions and two assessment tools the Zung Self-Rating Anxiety Scale (SAS) and the Zung Self-Rating Depression Scale (SDS). The results of the Self-Rating Scales were statistically examined in association with sex, age, and level of education.
Results
A total of 205 anonymous subjects participated in this study, and no responses were excluded. In the study group, 78 (38.05%) participants were male, and 127 (61.69%) were female. A higher tendency to anxiety was exhibited by female participants (p = 0.012) and the age group under 30 years of age (p = 0.042). The level of education has been identified as a significant factor for changes in mental state, as participants with higher levels of education tended to be in a worse mental state (p = 0.006).
Conclusions
Summarizing two years of the COVID-19 pandemic, the mental state of people with higher levels of education tended to feel worse, while females and younger adults felt more anxiety.
Journal Article
African voices on slavery and the slave trade. Volume 2, Essays on sources and methods
To cast light on African perspectives of the history of slavery, top Africanist scholars have examined both conventional historical sources and less-explored sources of information. This is the first of two volumes providing a trove of African sources for studying African slavery and slave trade.
Book
Universal nanodroplet branches from confining the Ouzo effect
We report the self-organization of universal branching patterns of oil nanodroplets under the Ouzo effect [Vitale S, Katz J (2003) Langmuir 19:4105–4110]—a phenomenon in which spontaneous droplet formation occurs upon dilution of an organic solution of oil with water. The mixing of the organic and aqueous phases is confined under a quasi-2D geometry. In a manner analogous to the ramification of ground stream networks [Devauchelle O, Petroff AP, Seybold HF, Rothman DH (2012) Proc Natl Acad Sci USA 109: 20832–20836 and Cohen Y, et al. (2015) Proc Natl Acad Sci USA 112:14132–14137] but on a scale 10 orders of magnitude smaller, the angles between the droplet branches are seen to exhibit remarkable universality, with a value around 74° ± 2°, independent of the various control parameters of the process. Numerical simulations reveal that these nanodroplet branching patterns are governed by the interplay between the local concentration gradient, diffusion, and collective interactions. We further demonstrate the ability of the local concentration gradient to drive autonomous motion of colloidal particles in the highly confined space, and the possibility of using the nucleated nanodroplets for nanoextraction of a hydrophobic solute. The understanding obtained from this work provides a basis for quantitatively understanding the complex dynamical aspects associated with the Ouzo effect. We expect that this will facilitate improved control in nanodroplet formation for many applications, spanning from the preparation of pharmaceutical polymeric carriers, to the formulation of cosmetics and insecticides, to the fabrication of nanostructured materials, to the concentration and separation of trace analytes in liquid–liquid microextraction.
Journal Article
Hirschsprung’s Disease—Recent Understanding of Embryonic Aspects, Etiopathogenesis and Future Treatment Avenues
Hirschsprung’s disease is a neurocristopathy, caused by defective migration, proliferation, differentiation and survival of neural crest cells, leading to gut aganglionosis. It usually manifests rapidly after birth, affecting 1 in 5000 live births around the globe. In recent decades, there has been a significant improvement in the understanding of its genetics and the association with other congenital anomalies, which share the pathomechanism of improper development of the neural crest. Apart from that, several cell populations which do not originate from the neural crest, but contribute to the development of Hirschsprung’s disease, have also been described, namely mast cells and interstitial cells of Cajal. From the diagnostic perspective, researchers also focused on “Variants of Hirschsprung’s disease”, which can mimic the clinical signs of the disease, but are in fact different entities, with distinct prognosis and treatment approaches. The treatment of Hirschsprung’s disease is usually surgical resection of the aganglionic part of the intestine, however, as many as 30–50% of patients experience persisting symptoms. Considering this fact, this review article also outlines future hopes and perspectives in Hirschsprung’s disease management, which has the potential to benefit from the advancements in the fields of cell-based therapy and tissue engineering.
Journal Article
Magnetic Induction Tomography: Separation of the Ill-Posed and Non-Linear Inverse Problem into a Series of Isolated and Less Demanding Subproblems
Magnetic induction tomography (MIT) is based on remotely excited eddy currents inside a measurement object. The conductivity distribution shapes the eddies, and their secondary fields are detected and used to reconstruct the conductivities. While the forward problem from given conductivities to detected signals can be unambiguously simulated, the inverse problem from received signals back to searched conductivities is a non-linear ill-posed problem that compromises MIT and results in rather blurry imaging. An MIT inversion is commonly applied over the entire process (i.e., localized conductivities are directly determined from specific signal features), but this involves considerable computation. The present more theoretical work treats the inverse problem as a non-retroactive series of four individual subproblems, each one less difficult by itself. The decoupled tasks yield better insights and control and promote more efficient computation. The overall problem is divided into an ill-posed but linear problem for reconstructing eddy currents from given signals and a nonlinear but benign problem for reconstructing conductivities from given eddies. The separated approach is unsuitable for common and circular MIT designs, as it merely fits the data structure of a recently presented and planar 3D MIT realization for large biomedical phantoms. For this MIT scanner, in discretization, the number of unknown and independent eddy current elements reflects the number of ultimately searched conductivities. For clarity and better representation, representative 2D bodies are used here and measured at the depth of the 3D scanner. The overall difficulty is not substantially smaller or different than for 3D bodies. In summary, the linear problem from signals to eddies dominates the overall MIT performance.
Journal Article
Laser-induced forward transfer of viscoplastic fluids
Laser-induced forward transfer (LIFT) is a nozzle-free printing technology that can be used for two- and three-dimensional printing. In LIFT, a laser pulse creates an impulse inside a thin film of material that results in the formation of a liquid jet. We experimentally study LIFT of viscoplastic materials by visualizing the process of jetting with high-speed imaging. The shape of the jet depends on the laser energy, focal height, surface tension and material rheology. We theoretically identify the characteristic jetting velocity and how it depends on the control parameters, and define non-dimensional groups to classify the regimes of jetting. Based on the results, we propose the optimal conditions for printing with LIFT technology.
Journal Article
A Deep Residual Neural Network for Image Reconstruction in Biomedical 3D Magnetic Induction Tomography
In recent years, it has become increasingly popular to solve inverse problems of various tomography methods with deep learning techniques. Here, a deep residual neural network (ResNet) is introduced to reconstruct the conductivity distribution of a biomedical, voluminous body in magnetic induction tomography (MIT). MIT is a relatively new, contactless and noninvasive tomography method. However, the ill-conditioned inverse problem of MIT is challenging to solve, especially for voluminous bodies with conductivities in the range of biological tissue. The proposed ResNet can reconstruct up to two cuboid perturbation objects with conductivities of 0.0 and 1.0 S/m in the whole voluminous body, even in the difficult-to-detect centre. The dataset used for training and testing contained simulated signals of cuboid perturbation objects with randomised lengths and positions. Furthermore, special care went into avoiding the inverse crime while creating the dataset. The calculated metrics showed good results over the test dataset, with an average correlation coefficient of 0.87 and mean squared error of 0.001. Robustness was tested on three special test cases containing unknown shapes, conductivities and a real measurement that showed error results well within the margin of the metrics of the test dataset. This indicates that a good approximation of the inverse function in MIT for up to two perturbation objects was achieved and the inverse crime was avoided.
Journal Article