The European Union (EU) initiative on the Digital Transformation of Health and Care (Digicare) aims to provide the conditions necessary for building a secure, flexible, and decentralized digital health infrastructure. Creating a European Health Research and Innovation Cloud (HRIC) within this environment should enable data sharing and analysis for health research across the EU, in compliance with data protection legislation while preserving the full trust of the participants. Such a HRIC should learn from and build on existing data infrastructures, integrate best practices, and focus on the concrete needs of the community in terms of technologies, governance, management, regulation, and ethics requirements. Here, we describe the vision and expected benefits of digital data sharing in health research activities and present a roadmap that fosters the opportunities while answering the challenges of implementing a HRIC. For this, we put forward five specific recommendations and action points to ensure that a European HRIC: i) is built on established standards and guidelines, providing cloud technologies through an open and decentralized infrastructure; ii) is developed and certified to the highest standards of interoperability and data security that can be trusted by all stakeholders; iii) is supported by a robust ethical and legal framework that is compliant with the EU General Data Protection Regulation (GDPR); iv) establishes a proper environment for the training of new generations of data and medical scientists; and v) stimulates research and innovation in transnational collaborations through public and private initiatives and partnerships funded by the EU through Horizon 2020 and Horizon Europe.

We introduce the synthesis and characterization of a novel purine derivative, 2-amino-6‑chloro-N,N-diphenyl-7H-purine-7-carboxamide. X-ray crystallography was utilized to elucidate its molecular and crystal structure. A comprehensive crystal packing analysis uncovered a network of diverse intermolecular interactions, including classical and unconventional hydrogen bonding. Remarkably, a unique halogen···π (C—Cl···π(ring)) interaction was identified and theoretically analyzed within a multi-approach quantum mechanics (QM) framework, revealing its lone-pair⋯π (n→π*) nature. Furthermore, insights into the electronic and chemical reactivity properties are provided by means of Conceptual Density Functional Theory (CDFT) at wB97X-D/aug-cc-pVTZ level. The compound's drug-likeness, pharmacokinetics, and toxicology profiles are assessed using ADMETlab 2.0. Finally, molecular docking simulations were conducted to evaluate its bioactivity as a potential cyclooxygenase-2 (COX-2) inhibitor. This study significantly advances our understanding of purine structure and reactivity, offering valuable insights for the development of targeted purine-based COX-2 inhibitors and anticancer therapeutics.

Three-dimensional (3D) tumor spheroids are regarded as promising models for utilization as preclinical assessments of chemo-sensitivity. However, the creation of these tumor spheroids presents challenges, given that not all tumor cell lines are able to form consistent and regular spheroids. In this context, we have developed a novel layer-by-layer coating of cellulose nanofibril–polyelectrolyte bilayers for the generation of spheroids. This technique builds bilayers of cellulose nanofibrils and polyelectrolytes and is used here to coat two distinct 96-well plate types: nontreated/non-sterilized and Nunclon Delta. In this work, we optimized the protocol aimed at generating and characterizing spheroids on difficult-to-grow pancreatic tumor cell lines. Here, diverse parameters were explored, encompassing the bilayer count (five and ten) and multiple cell-seeding concentrations (10, 100, 200, 500, and 1000 cells per well), using four pancreatic tumor cell lines—KPCT, PANC-1, MiaPaCa-2, and CFPAC-I. The evaluation includes the quantification (number of spheroids, size, and morphology) and proliferation of the produced spheroids, as well as an assessment of their viability. Notably, our findings reveal a significant influence from both the number of bilayers and the plate type used on the successful formation of spheroids. The novel and simple layer-by-layer-based coating method has the potential to offer the large-scale production of spheroids across a spectrum of tumor cell lines.

Pituitary neuroendocrine tumors (PitNETs) are common, generally benign tumors with complex clinical characteristics related to hormone hypersecretion and/or growing sellar tumor mass. PitNETs can be classified based on the expression pattern of anterior pituitary hormones and three main transcriptions factors (TF), SF1, PIT1 and TPIT that regulate differentiation of adenohypophysial cells. Here, we have extended this classification based on the global transcriptomics landscape using tumor tissue from a well-defined cohort comprising 51 PitNETs of different clinical and histological types. The molecular profiles were compared with current classification schemes based on immunohistochemistry. Our results identified three main clusters of PitNETs that were aligned with the main pituitary TFs expression patterns. Our analyses enabled further identification of specific genes and expression patterns, including both known and unknown genes, that could distinguish the three different classes of PitNETs. We conclude that the current classification of PitNETs based on the expression of SF1, PIT1 and TPIT reflects three distinct subtypes of PitNETs with different underlying biology and partly independent from the expression of corresponding hormones. The transcriptomic analysis reveals several potentially targetable tumor-driving genes with previously unknown role in pituitary tumorigenesis.

Given the need for modern researchers to produce open, reproducible scientific output, the lack of standards and best practices for sharing data and workflows used to produce and analyze molecular dynamics (MD) simulations has become an important issue in the field. There are now multiple well-established packages to perform molecular dynamics simulations, often highly tuned for exploiting specific classes of hardware, each with strong communities surrounding them, but with very limited interoperability/transferability options. Thus, the choice of the software package often dictates the workflow for both simulation production and analysis. The level of detail in documenting the workflows and analysis code varies greatly in published work, hindering reproducibility of the reported results and the ability for other researchers to build on these studies. An increasing number of researchers are motivated to make their data available, but many challenges remain in order to effectively share and reuse simulation data. To discuss these and other issues related to best practices in the field in general, we organized a workshop in November 2018 (https://bioexcel.eu/events/workshop-on-sharing-data-from-molecular-simulations/). Here, we present a brief overview of this workshop and topics discussed. We hope this effort will spark further conversation in the MD community to pave the way toward more open, interoperable, and reproducible outputs coming from research studies using MD simulations.

GROMACS is one of the most widely used open-source and free software codes in chemistry, used primarily for dynamical simulations of biomolecules. It provides a rich set of calculation types, preparation and analysis tools. Several advanced techniques for free-energy calculations are supported. In version 5, it reaches new performance heights, through several new and enhanced parallelization algorithms. These work on every level; SIMD registers inside cores, multithreading, heterogeneous CPU–GPU acceleration, state-of-the-art 3D domain decomposition, and ensemble-level parallelization through built-in replica exchange and the separate Copernicus framework. The latest best-in-class compressed trajectory storage format is supported.

Background Low total diversity of the gut microbiota during the first year of life is associated with allergic diseases in infancy, but little is known how early microbial diversity is related to allergic disease later in school age. Objective To assess microbial diversity and characterize the dominant bacteria in stool during the first year of life in relation to the prevalence of different allergic diseases in school age, such as asthma, allergic rhinoconjunctivitis (ARC) and eczema. Methods The microbial diversity and composition was analysed with barcoded 16S rDNA 454 pyrosequencing in stool samples at 1week, 1month and 12months of age in 47 infants which were subsequently assessed for allergic disease and skin prick test reactivity at 7years of age (ClinicalTrials.gov ID NCT01285830). Results Children developing asthma (n=8) had a lower diversity of the total microbiota than non-asthmatic children at 1week (P=0.04) and 1month (P=0.003) of age, whereas allergic rhinoconjunctivitis (n=13), eczema (n=12) and positive skin prick reactivity (n=14) at 7years of age did not associate with the gut microbiota diversity. Neither was asthma associated with the microbiota composition later in infancy (at 12months). Children having IgE-associated eczema in infancy and subsequently developing asthma had lower microbial diversity than those that did not. There were no significant differences, however, in relative abundance of bacterial phyla and genera between children with or without allergic disease. Conclusion and Clinical Relevance Low total diversity of the gut microbiota during the first month of life was associated with asthma but not ARC in children at 7years of age. Measures affecting microbial colonization of the infant during the first month of life may impact asthma development in childhood.

BACKGROUND: It is debated whether a low total diversity of the gut microbiota in early childhood is more important than an altered prevalence of particular bacterial species for the increasing incidence of allergic disease. The advent of powerful, cultivation-free molecular methods makes it possible to characterize the total microbiome down to the genus level in large cohorts. OBJECTIVE: We sought to assess microbial diversity and characterize the dominant bacteria in stool during the first year of life in relation to atopic eczema development. METHODS: Microbial diversity and composition were analyzed with barcoded 16S rDNA 454-pyrosequencing in stool samples at 1 week, 1 month, and 12 months of age in 20 infants with IgE-associated eczema and 20 infants without any allergic manifestation until 2 years of age (ClinicalTrials.gov ID NCT01285830). RESULTS: Infants with IgE-associated eczema had a lower diversity of the total microbiota at 1 month (P= .004) and a lower diversity of the bacterial phylum Bacteroidetes and the genus Bacteroides at 1 month (P= .02 and P= .01) and the phylum Proteobacteria at 12 months of age (P= .02). The microbiota was less uniform at 1 month than at 12 months of age, with a high interindividual variability. At 12 months, when the microbiota had stabilized, Proteobacteria, comprising gram-negative organisms, were more abundant in infants without allergic manifestation (Empirical Analysis of Digital Gene Expression in R edgeR test: P= .008, q= 0.02). CONCLUSION: Low intestinal microbial diversity during the first month of life was associated with subsequent atopic eczema.

Acyl protein thioesterase APT2 interacts with membranes via its charged beta-tongue, becomes palmitoylated by ZDHHC3/7 and deforms the bilayer to extract substrate acyl chains. APT2 deacylation leads to its membrane release and degradation. Many biochemical reactions require controlled recruitment of proteins to membranes. This is largely regulated by posttranslational modifications. A frequent one is S-acylation, which consists of the addition of acyl chains and can be reversed by poorly understood acyl protein thioesterases (APTs). Using a panel of computational and experimental approaches, we dissect the mode of action of the major cellular thioesterase APT2 (LYPLA2). We show that soluble APT2 is vulnerable to proteasomal degradation, from which membrane binding protects it. Interaction with membranes requires three consecutive steps: electrostatic attraction, insertion of a hydrophobic loop and S-acylation by the palmitoyltransferases ZDHHC3 or ZDHHC7. Once bound, APT2 is predicted to deform the lipid bilayer to extract the acyl chain bound to its substrate and capture it in a hydrophobic pocket to allow hydrolysis. This molecular understanding of APT2 paves the way to understand the dynamics of APT2-mediated deacylation of substrates throughout the endomembrane system.

Recent understandings in the development and spread of cancer have led to the realization of novel single cell analysis platforms focused on circulating tumor cells (CTCs). A simple, rapid, and inexpensive analytical platform capable of providing genetic information on these rare cells is highly desirable to support clinicians and researchers alike to either support the selection or adjustment of therapy or provide fundamental insights into cell function and cancer progression mechanisms. We report on the genetic profiling of single cancer cells, exploiting a combination of multiplex ligation-dependent probe amplification (MLPA) and electrochemical detection. Cells were isolated using laser capture and lysed, and the mRNA was extracted and transcribed into DNA. Seven markers were amplified by MLPA, which allows for the simultaneous amplification of multiple targets with a single primer pair, using MLPA probes containing unique barcode sequences. Capture probes complementary to each of these barcode sequences were immobilized on a printed circuit board (PCB) manufactured electrode array and exposed to single-stranded MLPA products and subsequently to a single stranded DNA reporter probe bearing a HRP molecule, followed by substrate addition and fast electrochemical pulse amperometric detection. We present asimple, rapid, flexible, and inexpensive approach for the simultaneous quantification of multiple breast cancer related mRNA markers, with single tumor cell sensitivity.

The hydrogen fuel cell vehicle market is projected to increase in the coming years, and fuel cell vehicles will operate in an environment where they coexist with combustion engine vehicles. In this context, the PEM fuel cell will be exposed to significant amounts of contaminants on the roads that will decrease its performance and durability. In the present study the PEM fuel cell is exposed to 100 ppm of nitrogen dioxide in the airflow. Different methods for recovery of performance were tested; recovery during constant current load and by subjecting the cell to successive polarization curves. The results showed that the successive polarization curves are the best choice for recovery. However, recovery at low current density and high potential is also a good alternative.

Angiotensin-converting enzyme 2 (ACE2) and accessory proteases (TMPRSS2 and CTSL) are needed for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) cellular entry, and their expression may shed light on viral tropism and impact across the body. We assessed the cell-type-specific expression of ACE2, TMPRSS2 and CTSL across 107 single-cell RNA-sequencing studies from different tissues. ACE2, TMPRSS2 and CTSL are coexpressed in specific subsets of respiratory epithelial cells in the nasal passages, airways and alveoli, and in cells from other organs associated with coronavirus disease 2019 (COVID-19) transmission or pathology. We performed a meta-analysis of 31 lung single-cell RNA-sequencing studies with 1,320,896 cells from 377 nasal, airway and lung parenchyma samples from 228 individuals. This revealed cell-type-specific associations of age, sex and smoking with expression levels of ACE2, TMPRSS2 and CTSL. Expression of entry factors increased with age and in males, including in airway secretory cells and alveolar type 2 cells. Expression programs shared by ACE2(+)TMPRSS2(+) cells in nasal, lung and gut tissues included genes that may mediate viral entry, key immune functions and epithelial-macrophage cross-talk, such as genes involved in the interleukin-6, interleukin-1, tumor necrosis factor and complement pathways. Cell-type-specific expression patterns may contribute to the pathogenesis of COVID-19, and our work highlights putative molecular pathways for therapeutic intervention.

An integrated analysis of over 100 single-cell and single-nucleus transcriptomics studies illustrates severe acute respiratory syndrome coronavirus 2 viral entry gene coexpression patterns across different human tissues, and shows association of age, smoking status and sex with viral entry gene expression in respiratory cell populations.

The Human Proteome Organization (HUPO) launched the Human Proteome Project (HPP) in 2010, creating an international framework for global collaboration, data sharing, quality assurance and enhancing accurate annotation of the genome-encoded proteome. During the subsequent decade, the HPP established collaborations, developed guidelines and metrics, and undertook reanalysis of previously deposited community data, continuously increasing the coverage of the human proteome. On the occasion of the HPP's tenth anniversary, we here report a 90.4% complete high-stringency human proteome blueprint. This knowledge is essential for discerning molecular processes in health and disease, as we demonstrate by highlighting potential roles the human proteome plays in our understanding, diagnosis and treatment of cancers, cardiovascular and infectious diseases. The Human Proteome Project (HPP) was launched in 2010 to enhance accurate annotation of the genome-encoded proteome. Ten years later, the HPP releases its first blueprint of the human proteome, annotating 90% of all known proteins at high-stringency and discussing the implications of proteomics for precision medicine.

To develop novel strategies for prevention and treatment of dyslipidemia, it is essential to understand the pathophysiology of dyslipoproteinemia in humans. Lipoprotein metabolism is a complex system in which abnormal concentrations of various lipoprotein particles can result from alterations in their rates of production, conversion, and/or catabolism. Traditional methods that measure plasma lipoprotein concentrations only provide static estimates of lipoprotein metabolism and hence limited mechanistic information. By contrast, the use of tracers labeled with stable isotopes and mathematical modeling, provides us with a powerful tool for probing lipid and lipoprotein kinetics in vivo and furthering our understanding of the pathogenesis of dyslipoproteinemia.

According to single-molecule localisation microscopy almost all plasma membrane proteins are clustered. We demonstrate that clusters can arise from variations in membrane topography where the local density of a randomly distributed membrane molecule to a degree matches the variations in the local amount of membrane. Further, we demonstrate that this false clustering can be differentiated from genuine clustering by using a membrane marker to report on local variations in the amount of membrane. In dual colour live cell single molecule localisation microscopy using the membrane probe DiI alongside either the transferrin receptor or the GPI-anchored protein CD59, we found that pair correlation analysis reported both proteins and DiI as being clustered, as did its derivative pair correlation-photoactivation localisation microscopy and nearest neighbour analyses. After converting the localisations into images and using the DiI image to factor out topography variations, no CD59 clusters were visible, suggesting that the clustering reported by the other methods is an artefact. However, the TfR clusters persisted after topography variations were factored out. We demonstrate that membrane topography variations can make membrane molecules appear clustered and present a straightforward remedy suitable as the first step in the cluster analysis pipeline. Variations in membrane topography can lead to the overestimation of protein clustering which can be avoided using a second image of a membrane marker, demonstrated with simulations and live cell SMLM.

Neuropeptide S (NPS) is a regulatory peptide with potent pharmacological effects. In rodents, NPS is expressed in a few pontine cell clusters. Its receptor (NPSR1) is, however, widely distributed in the brain. The anxiolytic and arousal promoting effects of NPS make the NPS NPSR1 system an interesting potential drug target in mood-related disorders. However, so far possible disease-related mechanisms involving NPS have only been studied in rodents. To validate the relevance of these animal studies for i.a. drug development, we have explored the distribution of NPS-expressing neurons in the human pons using in situ hybridization and stereological methods and we compared the distribution of NPS mRNA expressing neurons in the human and rat brain. The calculation revealed a total number of 22,317 +/- 2411 NPS mRNA-positive neurons in human, bilaterally. The majority of cells (84%) were located in the parabrachial area in human: in the extension of the medial and lateral parabrachial nuclei, in the Kolliker-Fuse nucleus and around the adjacent lateral lemniscus. In human, in sharp contrast to the rodents, only very few NPS-positive cells (5%) were found close to the locus coeruleus. In addition, we identified a smaller cell cluster (11% of all NPS cells) in the pontine central gray matter both in human and rat, which has not been described previously even in rodents. We also examined the distribution of NPSR1 mRNA-expressing neurons in the human pons. These cells were mainly located in the rostral laterodorsal tegmental nucleus, the cuneiform nucleus, the microcellular tegmental nucleus region and in the periaqueductal gray. Our results show that both NPS and NPSR1 in the human pons are preferentially localized in regions of importance for integration of visceral autonomic information and emotional behavior. The reported interspecies differences must, however, be considered when looking for targets for new pharmacotherapeutical interventions.

Neuropeptide S (NPS) is a regulatory peptide expressed by limited number of neurons in the brainstem. The simultaneous anxiolytic and arousal-promoting effect of NPS suggests an involvement in mood control and vigilance, making the NPS-NPS receptor system an interesting potential drug target. Here we examined, in detail, the distribution of NPS-immunoreactive (IR) fiber arborizations in brain regions of rat known to be involved in the regulation of sleep and arousal. Such nerve terminals were frequently apposed to GABAergic/galaninergic neurons in the ventro-lateral preoptic area (VLPO) and to tyrosine hydroxylase-IR neurons in all hypothalamic/thalamic dopamine cell groups. Then we applied the single platform-on-water (mainly REM) sleep deprivation method to study the functional role of NPS in the regulation of arousal. Of the three pontine NPS cell clusters, the NPS transcript levels were increased only in the peri-coerulear group in sleep-deprived animals, but not in stress controls. The density of NPS-IR fibers was significantly decreased in the median preoptic nucleus-VLPO region after the sleep deprivation, while radioimmunoassay and mass spectrometry measurements showed a parallel increase of NPS in the anterior hypothalamus. The expression of the NPS receptor was, however, not altered in the VLPO-region. The present results suggest a selective activation of one of the three NPS-expressing neuron clusters as well as release of NPS in distinct forebrain regions after sleep deprivation. Taken together, our results emphasize a role of the peri-coerulear cluster in the modulation of arousal, and the importance of preoptic area for the action of NPS on arousal and sleep.

Hepatic nerves have a complex role in synchronizing liver metabolism. Here, we used three-dimensional (3D) immunoimaging to explore the integrity of the hepatic nervous system in experimental and human nonalcoholic fatty liver disease (NAFLD). We demonstrate parallel signs of mild degeneration and axonal sprouting of sympathetic innervations in early stages of experimental NAFLD and a collapse of sympathetic arborization in steatohepatitis. Human fatty livers display a similar pattern of sympathetic nerve degeneration, correlating with the severity of NAFLD pathology. We show that chronic sympathetic hyperexcitation is a key factor in the axonal degeneration, here genetically phenocopied in mice deficient of the Rac-1 activator Vav3. In experimental steatohepatitis, 3D imaging reveals a severe portal vein contraction, spatially correlated with the extension of the remaining nerves around the portal vein, enlightening a potential intrahepatic neuronal mechanism of portal hypertension. These fundamental alterations in liver innervation and vasculature uncover previously unidentified neuronal components in NAFLD pathomechanisms.

Alzheimer's disease and other age-related neurodegenerative disorders are associated with deterioration of the noradrenergic locus coeruleus (LC), a probable trigger for mood and memory dysfunction. LC noradrenergic neurons exhibit particularly high levels of somatostatin binding sites. This is noteworthy since cortical and hypothalamic somatostatin content is reduced in neurodegenerative pathologies. Yet a possible role of a somatostatin signal deficit in the maintenance of noradrenergic projections remains unknown. Here, we deployed tissue microarrays, immunohistochemistry, quantitative morphometry and mRNA profiling in a cohort of Alzheimer's and age-matched control brains in combination with genetic models of somatostatin receptor deficiency to establish causality between defunct somatostatin signalling and noradrenergic neurodegeneration. In Alzheimer's disease, we found significantly reduced somatostatin protein expression in the temporal cortex, with aberrant clustering and bulging of tyrosine hydroxylase-immunoreactive afferents. As such, somatostatin receptor 2 (SSTR2) mRNA was highly expressed in the human LC, with its levels significantly decreasing from Braak stages III/IV and onwards, i.e., a process preceding advanced Alzheimer's pathology. The loss of SSTR2 transcripts in the LC neurons appeared selective, since tyrosine hydroxylase, dopamine beta-hydroxylase, galanin or galanin receptor 3 mRNAs remained unchanged. We modeled these pathogenic changes in Sstr2 (-/-) mice and, unlike in Sstr1 (-/-) or Sstr4 (-/-) genotypes, they showed selective, global and progressive degeneration of their central noradrenergic projections. However, neuronal perikarya in the LC were found intact until late adulthood (< 8 months) in Sstr2 (-/-) mice. In contrast, the noradrenergic neurons in the superior cervical ganglion lacked SSTR2 and, as expected, the sympathetic innervation of the head region did not show any signs of degeneration. Our results indicate that SSTR2-mediated signaling is integral to the maintenance of central noradrenergic projections at the system level, and that early loss of somatostatin receptor 2 function may be associated with the selective vulnerability of the noradrenergic system in Alzheimer's disease.

Abbreviations: VMN/PVN, hypothalamic ventromedial nucleus/paraventricular nucleus; VLM/VMM, ventrolateral medulla/ventromedial medulla; SMG/CG, superior mesenteric ganglion/caeliac ganglia; NTS, nucleus of the solitary tract; NG, nodose ganglion. Nonalcoholic fatty liver disease (NAFLD) is the most common chronic liver disorder. Increased sympathetic (noradrenergic) nerve tone has a complex role in the etiopathomechanism of NAFLD, affecting the development/progression of steatosis, inflammation, fibrosis, and liver hemodynamical alterations. Also, lipid sensing by vagal afferent fibers is an important player in the development of hepatic steatosis. Moreover, disorganization and progressive degeneration of liver sympathetic nerves were recently described in human and experimental NAFLD. These structural alterations likely come along with impaired liver sympathetic nerve functionality and lack of adequate hepatic noradrenergic signaling. Here, we first overview the anatomy and physiology of liver nerves. Then, we discuss the nerve impairments in NAFLD and their pathophysiological consequences in hepatic metabolism, inflammation, fibrosis, and hemodynamics. We conclude that further studies considering the spatial-temporal dynamics of structural and functional changes in the hepatic nervous system may lead to more targeted pharmacotherapeutic advances in NAFLD.

Despite decades of accumulated knowledge about proteins and their post-translational modifications (PTMs), numerous questions remain regarding their molecular composition and biological function. One of the most fundamental queries is the extent to which the combinations of DNA-, RNA-and PTM-level variations explode the complexity of the human proteome. Here, we outline what we know from current databases and measurement strategies including mass spectrometry-based proteomics. In doing so, we examine prevailing notions about the number of modifications displayed on human proteins and how they combine to generate the protein diversity underlying health and disease. We frame central issues regarding determination of protein-level variation and PTMs, including some paradoxes present in the field today. We use this framework to assess existing data and to ask the question, "How many distinct primary structures of proteins (proteoforms) are created from the 20,300 human genes?" We also explore prospects for improving measurements to better regularize protein-level biology and efficiently associate PTMs to function and phenotype.

Motivation: Liquid chromatography is frequently used as a means to reduce the complexity of peptide-mixtures in shotgun proteomics. For such systems, the time when a peptide is released from a chromatography column and registered in the mass spectrometer is referred to as the peptide's retention time. Using heuristics or machine learning techniques, previous studies have demonstrated that it is possible to predict the retention time of a peptide from its amino acid sequence. In this paper, we are applying Gaussian Process Regression to the feature representation of a previously described predictor ELUDE. Using this framework, we demonstrate that it is possible to estimate the uncertainty of the prediction made by the model. Here we show how this uncertainty relates to the actual error of the prediction. Results: In our experiments, we observe a strong correlation between the estimated uncertainty provided by Gaussian Process Regression and the actual prediction error. This relation provides us with new means for assessment of the predictions. We demonstrate how a subset of the peptides can be selected with lower prediction error compared to the whole set. We also demonstrate how such predicted standard deviations can be used for designing adaptive windowing strategies.

Coronavirus disease 2019 (COVID-19) is caused by a novel virus named Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2). This virus induced a large number of deaths and millions of confirmed cases worldwide, creating a serious danger to public health. However, there are no specific therapies or drugs available for COVID-19 treatment. While new drug discovery is a long process, repurposing available drugs for COVID-19 can help recognize treatments with known clinical profiles. Computational drug repurposing methods can reduce the cost, time, and risk of drug toxicity. In this work, we build a graph as a COVID-19 related biological network. This network is related to virus targets or their associated biological processes. We select essential proteins in the constructed biological network that lead to a major disruption in the network. Our method from these essential proteins chooses 93 proteins related to COVID-19 pathology. Then, we propose multiple informative features based on drug-target and protein-protein interaction information. Through these informative features, we find five appropriate clusters of drugs that contain some candidates as potential COVID-19 treatments. To evaluate our results, we provide statistical and clinical evidence for our candidate drugs. From our proposed candidate drugs, 80% of them were studied in other studies and clinical trials.

Sexual dimorphism has been used to describe morphological differences between the sexes, but can be extended to any biologically related process that varies between males and females. The synaptonemal complex (SC) is a tripartite structure that connects homologous chromosomes in meiosis. Here, aided by superresolution microscopy techniques, we show that the SC is subject to sexual dimorphism, in mouse germ cells. We have identified a significantly narrower SC in oocytes and have established that this difference does not arise from a different organization of the lateral elements nor from a different isoform of transverse filament protein SYCP1. Instead, we provide evidence for the existence of a narrower central element and a different integration site for the C-termini of SYCP1, in females. In addition to these female-specific features, we speculate that post-translation modifications affecting the SYCP1 coiled-coil region could render a more compact conformation, thus contributing to the narrower SC observed in females.

During meiosis, cohesin complexes mediate sister chromatid cohesion (SCC), synaptonemal complex (SC) assembly and synapsis. Here, using super-resolution microscopy, we imaged sister chromatid axes in mouse meiocytes that have normal or reduced levels of cohesin complexes, assessing the relationship between localization of cohesin complexes, SCC and SC formation. We show that REC8 foci are separated from each other by a distance smaller than 15% of the total chromosome axis length in wild-type meiocytes. Reduced levels of cohesin complexes result in a local separation of sister chromatid axial elements (LSAEs), as well as illegitimate SC formation at these sites. REC8 but not RAD21 or RAD21L cohesin complexes flank sites of LSAEs, whereas RAD21 and RAD21L appear predominantly along the separated sister-chromatid axes. Based on these observations and a quantitative distribution analysis of REC8 along sister chromatid axes, we propose that the high density of randomly distributed REC8 cohesin complexes promotes SCC and prevents illegitimate SC formation.

Understanding functional effects of genetic variants is one of the key challenges in human genetics, as much of disease-associated variation is located in non-coding regions with typically unknown putative gene regulatory effects. One of the most important approaches in this field has been molecular quantitative trait locus (molQTL) mapping, where genetic variation is associated with molecular traits that can be measured at scale, such as gene expression, splicing and chromatin accessibility. The maturity of the field and large-scale studies have produced a rich set of established methods for molQTL analysis, with novel technologies opening up new areas of discovery. In this Primer, we discuss the study design, input data and statistical methods for molQTL mapping and outline the properties of the resulting data as well as popular downstream applications. We review both the limitations and caveats of molQTL mapping as well as future potential approaches to tackle them. With technological development now providing many complementary methods for functional characterization of genetic variants, we anticipate that molQTLs will remain an important part of this toolkit as the only existing approach that can measure human variation in its native genomic, cellular and tissue context.

In higher eukaryotes many genes encode protein isoforms whose properties and biological roles are often poorly characterized. Here we describe systematic approaches for detection of either distinct isoforms, or separate pools of the same isoform, with differential biological properties. Using information from ion intensities we have estimated protein abundance levels and using rates of change in stable isotope labeling with amino acids in cell culture isotope ratios we measured turnover rates and subcellular distribution for the HeLa cell proteome. Protein isoforms were detected using three data analysis strategies that evaluate differences between stable isotope labeling with amino acids in cell culture isotope ratios for specific groups of peptides within the total set of peptides assigned to a protein. The candidate approach compares stable isotope labeling with amino acids in cell culture isotope ratios for predicted isoform- specific peptides, with ratio values for peptides shared by all the isoforms. The rule of thirds approach compares the mean isotope ratio values for all peptides in each of three equal segments along the linear length of the protein, assessing differences between segment values. The three in a row approach compares mean isotope ratio values for each sequential group of three adjacent peptides, assessing differences with the mean value for all peptides assigned to the protein. Protein isoforms were also detected and their properties evaluated by fractionating cell extracts on one- dimensional SDS- PAGE prior to trypsin digestion and MS analysis and independently evaluating isotope ratio values for the same peptides isolated from different gel slices. The effect of protein phosphorylation on turnover rates was analyzed by comparing mean turnover values calculated for all peptides assigned to a protein, either including, or excluding, values for cognate phosphopeptides. Collectively, these experimental and analytical approaches provide a framework for expanding the func- tional annotation of the genome.

Accumulating evidence shows that oxidative stress is involved in a wide variety of human diseases: rheumatoid arthritis, Alzheimers disease, Parkinsons disease, cancers, etc. Here, we discuss the significance of oxidative conditions in different disease, with the focus on neurodegenerative disease including Parkinsons disease, which is mainly caused by oxidative stress. Reactive oxygen and nitrogen species (ROS and RNS, respectively), collectively known as RONS, are produced by cellular enzymes such as myeloperoxidase, NADPH-oxidase (nicotinamide adenine dinucleotide phosphate-oxidase) and nitric oxide synthase (NOS). Natural antioxidant systems are categorized into enzymatic and non-enzymatic antioxidant groups. The former includes a number of enzymes such as catalase and glutathione peroxidase, while the latter contains a number of antioxidants acquired from dietary sources including vitamin C, carotenoids, flavonoids and polyphenols. There are also scavengers used for therapeutic purposes, such as 3,4-dihydroxyphenylalanine (L-DOPA) used routinely in the treatment of Parkinsons disease (not as a free radical scavenger), and 3-methyl-1-phenyl-2-pyrazolin-5-one (Edaravone) that acts as a free radical detoxifier frequently used in acute ischemic stroke. The cell surviving properties of L-DOPA and Edaravone against oxidative stress conditions rely on the alteration of a number of stress proteins such as Annexin A1, Peroxiredoxin-6 and PARK7/DJ-1 (Parkinson disease protein 7, also known as Protein deglycase DJ-1). Although they share the targets in reversing the cytotoxic effects of H2O2, they seem to have distinct mechanism of function. Exposure to L-DOPA may result in hypoxia condition and further induction of ORP150 (150-kDa oxygen-regulated protein) with its concomitant cytoprotective effects but Edaravone seems to protect cells via direct induction of Peroxiredoxin-2 and inhibition of apoptosis.

Soil microorganisms living in close contact with minerals play key roles in the biogeochemical cycling of elements, soil formation, and plant nutrition. Yet, the composition of microbial communities inhabiting the mineralosphere (i.e., the soil surrounding minerals) is poorly understood. Here, we explored the composition of soil microbial communities associated with different types of minerals in various soil horizons. To this effect, a field experiment was set up in which mineral specimens of apatite, biotite, and oligoclase were buried in the organic, eluvial, and upper illuvial horizons of a podzol soil. After an incubation period of two years, the soil attached to the mineral surfaces was collected, and microbial communities were analyzed by means of Illumina MiSeq sequencing of the 16S (prokaryotic) and 18S (eukaryotic) ribosomal RNA genes. We found that both composition and diversity of bacterial, archaeal, and fungal communities varied across the different mineral surfaces, and that mineral type had a greater influence on structuring microbial assemblages than soil horizon. Thus, our findings emphasize the importance of mineral surfaces as ecological niches in soils.

Introduction: Inflammation is an important risk-associated component of many diseases and can be diagnosed by molecular imaging of specific molecules. The aim of this study was to evaluate the possibility of targeting adhesion molecules on inflammation-activated endothelial cells and macrophages using an innovative multimodal polyvinyl alcohol-based microbubble (MB) contrast agent developed for diagnostic use in ultrasound, magnetic resonance, and nuclear imaging. Methods: We assessed the binding efficiency of antibody-conjugated multimodal contrast to inflamed murine or human endothelial cells (ECs), and to peritoneal macrophages isolated from rats with peritonitis, utilizing the fluorescence characteristics of the MBs. Single-photon emission tomography (SPECT) was used to illustrate ^99m Tc-labeled MB targeting and distribution in an experimental in vivo model of inflammation. Results: Flow cytometry and confocal microscopy showed that binding of antibody-targeted MBs to the adhesion molecules ICAM-1, VCAM-1, or E-selectin, expressed on cytokine-stimulated ECs, was up to sixfold higher for human and 12-fold higher for mouse ECs, compared with that of non-targeted MBs. Under flow conditions, both VCAM-1- and E-selectin-targeted MBs adhered more firmly to stimulated human ECs than to untreated cells, while VCAM-1-targeted MBs adhered best to stimulated murine ECs. SPECT imaging showed an approximate doubling of signal intensity from the abdomen of rats with peritonitis, compared with healthy controls, after injection of anti-ICAM-1-MBs. Conclusions: This novel multilayer contrast agent can specifically target adhesion molecules expressed as a result of inflammatory stimuli in vitro, and has potential for use in disease-specific multimodal diagnostics in vivo using antibodies against targets of interest.

Molecular dynamics (MD) computer simulations are used routinely to compute atomistic trajectories of complex systems. Systems are simulated in various ensembles, depending on the experimental conditions one aims to mimic. While constant energy, temperature, volume, and pressure are rather straightforward to model, pH, which is an equally important parameter in experiments, is more difficult to account for in simulations. Although a constant pH algorithm based on the λ-dynamics approach by Brooks and co-workers [Kong, X.; Brooks III, C. L. J. Chem. Phys.1996, 105, 2414–2423] was implemented in a fork of the GROMACS molecular dynamics program, uptake has been rather limited, presumably due to the poor scaling of that code with respect to the number of titratable sites. To overcome this limitation, we implemented an alternative scheme for interpolating the Hamiltonians of the protonation states that makes the constant pH molecular dynamics simulations almost as fast as a normal MD simulation with GROMACS. In addition, we implemented a simpler scheme, called multisite representation, for modeling side chains with multiple titratable sites, such as imidazole rings. This scheme, which is based on constraining the sum of the λ-coordinates, not only reduces the complexity associated with parametrizing the intramolecular interactions between the sites but also is easily extendable to other molecules with multiple titratable sites. With the combination of a more efficient interpolation scheme and multisite representation of titratable groups, we anticipate a rapid uptake of constant pH molecular dynamics simulations within the GROMACS user community.

In vitro screening of large compound libraries with automated high-throughput screening is expensive and time-consuming and requires dedicated infrastructures. Conversely, the selection of DNA-encoded chemical libraries (DECLs) can be rapidly performed with routine equipment available in most laboratories. In this study, we identified novel inhibitors of SARS-CoV-2 main protease (Mpro) through the affinity-based selection of the DELopen library (open access for academics), containing 4.2 billion compounds. The identified inhibitors were peptide-like compounds containing an N-terminal electrophilic group able to form a covalent bond with the nucleophilic Cys145 of Mpro, as confirmed by x-ray crystallography. This DECL selection campaign enabled the discovery of the unoptimized compound SLL11 (IC50 = 30 nM), proving that the rapid exploration of large chemical spaces enabled by DECL technology allows for the direct identification of potent inhibitors avoiding several rounds of iterative medicinal chemistry. As demonstrated further by x-ray crystallography, SLL11 was found to adopt a highly unique U-shaped binding conformation, which allows the N-terminal electrophilic group to loop back to the S1′ subsite while the C-terminal amino acid sits in the S1 subsite. MP1, a close analog of SLL11, showed antiviral activity against SARS-CoV-2 in the low micromolar range when tested in Caco-2 and Calu-3 (EC50 = 2.3 µM) cell lines. As peptide-like compounds can suffer from low cell permeability and metabolic stability, the cyclization of the compounds will be explored in the future to improve their antiviral activity.

We here present a comparative genome, transcriptome and functional network analysis of three human cancer cell lines (A431, U251MG and U2OS), and investigate their relation to protein expression. Gene copy numbers significantly influenced corresponding transcript levels; their effect on protein levels was less pronounced. We focused on genes with altered mRNA and/or protein levels to identify those active in tumor maintenance. We provide comprehensive information for the three genomes and demonstrate the advantage of integrative analysis for identifying tumor-related genes amidst numerous background mutations by relating genomic variation to expression/protein abundance data and use gene networks to reveal implicated pathways.

Cancer and antibiotic-resistant bacterial infections are significant global health challenges. The resistance developed in cancer treatments intensifies therapeutic difficulties. In addressing these challenges, this study synthesised a series of N,N '-dialkyl urea derivatives containing methoxy substituents on phenethylamines. Using isocyanate for the efficient synthesis yielded target products 14-18 in 73-76% returns. Subsequently, their antibacterial and anticancer potentials were assessed. Cytotoxicity tests on cancer cell lines, bacterial strains, and a healthy fibroblast line revealed promising outcomes. All derivatives demonstrated robust antibacterial activity, with MIC values ranging from 0.97 to 15.82 mu M. Notably, compounds 14 and 16 were particularly effective against the HeLa cell line, while compounds 14, 15, and 17 showed significant activity against the SH-SY5Y cell line. Importantly, these compounds had reduced toxicity to healthy fibroblast cells than to cancer cells, suggesting their potential as dual-functioning agents targeting both cancer and bacterial infections.

Starting compound 1 was synthesized according to reference. 1 Benzylidene thiazole pyrimidin-3(5H)-ones were synthesized reactions of 1 with bromoacetic acid and various aryl-aldehydes in the same vessel via one-step, unlike studies in the literature. Quantum chemical parameters and full geometry optimizations for all compounds were computed using DFT based on B3LYP. Cytotoxic action potential of synthesized compounds was evaluated using trypan blue dye exclusion and MTT assays in different cell lines including adenocarcinoma alveolar basal epithelial-like adherent A549 cells, the colon adenocarcinoma HT-29 cells, prostate adenocarcinoma DU-145 cells, and diploid ARPE-19 retinal pigment epithelial cells. Embryotoxicity and genotoxicity assessments were performed on pluripotent human embryonal carcinoma NT2 and human lymphocyte cells, respectively. Compound A1 exhibited good anticancer activity on A549 and DU-145 cell lines, and the compounds including A3, 4, 6, and 9 induced cytotoxicity on A549 cells. The compounds A1-10 also showed a good biosafety profile at relatively lower concentrations.

In this study, phenyl (1,4,6-triphenyl-2-thioxo-1,2,3,4-tetrahydropyrimidin-5-yl)methanone was obtained by using the Biginelli reaction method. The structure of this compound was analyzed using elemental analysis, IR, 1H, and 13C NMR. The quantum chemical calculations (QCC) of this compound were performed density functional theory (DFT) method, 6–31 G (d, p) base set, and B3LYP functions with the Gaussian09W software package. Literature shows that pyrimidine-derived compounds have very active biological properties. For this reason, the biologically active properties of the synthesized compound were also examined. To determine embryotoxic, genotoxic, and cytotoxic effects of compound, 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl-2H-tetrazolium bromide (MTT), lactate dehydrogenase (LDH) release, micronucleus (MN) and 8-OH-dG assays were carried out. On the other hand, pharmacokinetic and toxicity properties (ADMET) were predicted in silico via SwissADME and Protox-II web tools. In silico estimates of this compound used in the study showed that the compound has the covetable physicochemical properties for bioavailability. In conclusion, the obtained results of our study clearly showed that this compound exerted strong toxicity potential.

Advancements in medical diagnostics have allowed us to understand the underlying mechanism and treat the root cause for many diseases which had been causing morbidity and mortality up until this point in human history. Furthermore, many of the standard diagnostic procedures have now been transformed to provide answers at or near the point-of-care. However, the effects of these positive developments have not trickled down to the parts of our society which are considered underdeveloped and lack the necessary infrastructure and facilities. Diagnostics in such resource limited settings still lag behind and fail to provide the requisite healthcare. 

In order to translate the diagnostic solutions designed for central laboratories to resource limited settings, there are certain challenges that need to be addressed, such as portability, reduction in cost and ease-of-use, while keeping the sensitivity and specificity at the required level. The work presented in this thesis focuses on addressing some of these issues by using microfluidics to develop diagnostic platforms that are suitable to be used in resource limited settings. 

In paper I, a very low-cost and simple centrifugal microfluidic platform was developed to be used in settings which do not have a reliable supply of electricity. The platform uses a smartphone as a source of power and the sensors of the phone for speed control.

In paper II, a portable and low-cost diagnostic platform was developed for multiplexed detection of biomarkers based on centrifugal microfluidics. The platform uses colorimetric detection and a simple readout method which does not require a spectrophotometer for quantification.

In paper III, a platform was developed for COVID-19 diagnostics which combines centrifugal microfluidics with a novel bead-based strategy for signal enhancement. The platform uses fluorescent detection with a smartphone readout and has the capability to process up to 20 samples at the same time.

In paper IV, as a follow up of paper III, a more advanced platform was developed for COVID-19 diagnostics which allows the operator to carry out nucleic acid amplification in a completely automated manner, from adding the sample to getting the final result.

In paper V, an alternative method for detection of SARS-CoV-2 was developed using electrochemical biosensing. This work combines the electrochemical technique with a flexible printed circuit board for a rapid, amplification-free and label-free detection of target SARS-CoV-2 sequences.

COVID-19 pandemic made it evident that the world is unprepared for effectively tackling a pandemic resulting from an infectious disease. The conventional diagnostic methods for detection of infectious diseases were limited to centralized laboratories. As the burden of testing increased with the spread of the disease, the centralized testing facilities were strained for resources and personnel. These problems were further exacerbated in low- and middle-income countries where the health and transport infrastructure are not very well developed. To overcome this reliance on centralized testing and to facilitate decentralized testing, focus was shifted towards development of novel point-of-care diagnostic methods. We report the development of a fully automated centrifugal microfluidic platform that uses loop mediated isothermal amplification (LAMP) combined with computer vision-based readout for COVID-19 detection. The integrated platform allows sample to answer analysis at the push of a single button and can process 26 samples in 40 minutes. The platform performs a completely automated assay protocol involving heating, rotation and detection without the need for user intervention. A limit of detection of approximately 100 RNA copies in 10 µL reaction was achieved using RNA fragments spiked in water and similar results were obtained for artificial saliva samples. 

The up- and down- regulation of inflammatory biomarkers such as cytokines can be indicative of several diseases such as primary cancers and/or metastatic tumors, as well as less serious conditions. For point-of-care clinical applications, the detection of these biomarkers requires a combination of a sensitive assay and multiplexing capabilities, together with fit-for-purpose signal transduction strategies. Here, we report the development of a versatile and cost-effective integrated centrifugal microfluidic platform compatible with resource-limited settings using nanoporous microbeads for immunoaffinity-based profiling of cytokines. With an automated colorimetric readout at the end, the platform allows for profiling of cytokines in < 30 mins.

The detection of panels of inflammatory biomarkers such as cytokines has potential for the rapid and specific diagnostic of several devastating diseases such as primary cancers and/or metastatic tumors, as opposed to less serious conditions. For point-of-care clinical applications, the detection of these biomarkers requires a combination of pg/mL sensitivities and multiplexing capabilities, coupled with fit-for-purpose signal transduction strategies. Here, we report the development of a versatile centrifugal microfluidic platform combined with nanoporous microbeads for immunoaffinity-based profiling of cytokines. The device allows sample and analyte multiplexing and detection limits below 1 ng/mL were achieved within 30 minutes, using colorimetric detection.

Cytokines play a very important role in our immune system by acting as mediators to put up a coordinated defense against foreign elements in our body. Elevated levels of cytokines in the body can signal to an ongoing response of the immune system to some abnormality. Thus, the quantification of a panel of cytokines can provide valuable information regarding the diagnosis of specific diseases and state of overall health of an individual. Conventional Enzyme Linked Immunosorbent Assay (ELISA) is the gold-standard for quantification of cytokines, however the need for trained personnel and expensive equipment limits its application to centralized laboratories only. In this context, there is a lack of simple, low-cost and portable devices which can allow for quantification of panels of cytokines at point-of-care and/or resource limited settings.

Here, we report the development of a versatile, low-cost and portable bead-based centrifugal microfluidic platform allowing for multiplexed detection of cytokines with minimal hands-on time and an integrated colorimetric signal readout without the need for any external equipment. As a model, multiplexed colorimetric quantification of three target cytokines i.e., Tumor necrosis factor alpha (TNF-α), Interferon gamma (IFN-γ) and Interleukin-2 (IL-2) was achieved in less than 30 min with limits of detection in ng/mL range. The developed platform was further evaluated using spiked-in plasma samples to test for matrix interference. The ease of use, low-cost and portability of the developed platform highlight its potential to serve as a sample-to-answer solution for detection of cytokine panels in resource limited settings.

Reproductive phase change is well characterized in angiosperm model species, but less studied in gymnosperms. We utilize the early cone-setting acrocona mutant to study reproductive phase change in the conifer Picea abies (Norway spruce), a gymnosperm. The acrocona mutant frequently initiates cone-like structures, called transition shoots, in positions where wild-type P. abies always produces vegetative shoots. We collect acrocona and wild-type samples, and RNA-sequence their messenger RNA (mRNA) and microRNA (miRNA) fractions. We establish gene expression patterns and then use allele-specific transcript assembly to identify mutations in acrocona. We genotype a segregating population of inbred acrocona trees. A member of the SQUAMOSA BINDING PROTEIN-LIKE (SPL) gene family, PaSPL1, is active in reproductive meristems, whereas two putative negative regulators of PaSPL1, miRNA156 and the conifer specific miRNA529, are upregulated in vegetative and transition shoot meristems. We identify a mutation in a putative miRNA156/529 binding site of the acrocona PaSPL1 allele and show that the mutation renders the acrocona allele tolerant to these miRNAs. We show co-segregation between the early cone-setting phenotype and trees homozygous for the acrocona mutation. In conclusion, we demonstrate evolutionary conservation of the age-dependent flowering pathway and involvement of this pathway in regulating reproductive phase change in the conifer P. abies. 

Recent efforts to sequence the genomes and transcriptomes of several gymnosperm species have revealed an increased complexity in certain gene families in gymnosperms as compared to angiosperms. One example of this is the gymnosperm sister Glade to angiosperm TM3-like MADS-box genes, which at least in the conifer lineage has expanded in number of genes. We have previously identified a member of this subclade, the conifer gene DEFICIENS AGAMOUS LIKE 19 (DAL19), as being specifically upregulated in cone-setting shoots. Here, we show through Sanger sequencing of mRNA-derived cDNA and mapping to assembled conifer genomic sequences that DAL19 produces six mature mRNA splice variants in Picea abies. These splice variants use alternate first and last exons, while their four central exons constitute a core region present in all six transcripts. Thus, they are likely to be transcript isoforms. Quantitative Real-Time PCR revealed that two mutually exclusive first DAL19 exons are differentially expressed across meristems that will form either male or female cones, or vegetative shoots. Furthermore, mRNA in situ hybridization revealed that two mutually exclusive last DAL19 exons were expressed in a cell-specific pattern within bud meristems. Based on these findings in DAL19, we developed a sensitive approach to transcript isoform assembly from short-read sequencing of mRNA. We applied this method to 42 putative MADS-box core regions in P abies, from which we assembled 1084 putative transcripts. We manually curated these transcripts to arrive at 933 assembled transcript isoforms of 38 putative MADS-box genes. 152 of these isoforms, which we assign to 28 putative MADS-box genes, were differentially expressed across eight female, male, and vegetative buds. We further provide evidence of the expression of 16 out of the 38 putative MADS-box genes by mapping PacBio Iso-Seq circular consensus reads derived from pooled sample sequencing to assembled transcripts. In summary, our analyses reveal the use of mutually exclusive exons of MADS-box gene isoforms during early bud development in P. abies, and we find that the large number of identified MADS-box transcripts in P. abies results not only from expansion of the gene family through gene duplication events but also from the generation of numerous splice variants.

Na⁺,K⁺-ATPase is one of the most important proteins in the mammalian cell. It creates sodium and potassium gradients which are fundamental for the membrane potential and sodium-dependent secondary active transport. It has a second role in the cell as a receptor that by binding chemicals from the cardiotonic steroids family, the most knowledgeable of them is ouabain, triggers various signaling pathways in the cell which regulate gene activation, proliferation, apoptosis, etc. It has been shown that several severe neurological diseases are associated with mutations in the Na⁺,K⁺-ATPase encoding genes. Although Na⁺,K⁺-ATPase was discovered already in 1957 by the Danish scientist Jens Skou, the knowledge about the function of this enzyme  is still not complete.

In the studies included in the thesis, we have learned more about the function of Na⁺,K⁺-ATPase in different aspects of health and disease. In study I we showed a mechanism of ouabain-dependent regulation of the NMDA receptor, one of the most important receptors in the nervous system, via binding with Na⁺,K⁺-ATPase. This allows us to look at the Na⁺,K⁺-ATPase as regulator via protein-protein interaction. In study II we investigated a different aspect of Na⁺,K⁺-ATPase functioning – to look at how binding of ouabain to Na⁺,K⁺-ATPase activates a number of signaling cascades by looking at the phosphoproteome status of the cells. This allows us to see the whole picture of ouabain-mediated cascades and further characterize them. In study III we focused on the role of Na⁺,K⁺-ATPase in severe epileptic encephalopathy caused by a mutation in the ATP1A1 gene. We performed a molecular and cellular study to describe how mutations affects protein structure and function and found that this mutation converts the ion pump to a nonspecific leak channel. In study IV we performed a translational study of the most common mutation for rapid-onset dystonia-parkinsonism. We studied how this mutation affects the nervous system on the protein-, cellular-, and organism level and found that the complete absence of ultraslow afterhyperpolarization (usAHP) could explain gait disturbances found in patients. In the on-going study we showed that Na⁺,K⁺-ATPase can oligomerize and that this effect is triggered by ouabain binding to the Na⁺,K⁺-ATPase. In this study, we utilized a novel fluorescence labelling approach and used biophysical techniques with single molecule sensitivity to track Na⁺,K⁺-ATPase interactions.

In summary, we applied biophysical and molecular methods to study different aspects of the function of Na⁺,K⁺-ATPase, and gained insights that could be helpful not only for answering fundamental questions about Na⁺,K⁺-ATPase but also to find a treatment for patients with diseases associated with mutations in this protein.

The N-methyl-D-aspartate (NMDA) receptor plays an essential role in glutamatergic transmission and synaptic plasticity and researchers are seeking for different modulators of NMDA receptor function. One possible mechanism for its regulation could be through adjacent membrane proteins. NMDA receptors coprecipitate with Na,K-ATPase, indicating a potential interaction of these two proteins. Ouabain, a mammalian cardiotonic steroid that specifically binds to Na,K-ATPase and affects its conformation, can protect from some toxic effects of NMDA receptor activation. Here we have examined whether NMDA receptor activity and downstream effects can be modulated by physiological ouabain concentrations. The spatial colocalization between NMDA receptors and the Na,K-ATPase catalytic subunits on dendrites of cultured rat hippocampal neurons was analyzed with super-resolution dSTORM microscopy. The functional interaction was analyzed with calcium imaging of single hippocampal neurons exposed to 10 μM NMDA in presence and absence of ouabain and by determination of the ouabain effect on NMDA receptor-dependent long-term potentiation. We show that NMDA receptors and the Na,K-ATPase catalytic subunits alpha1 and alpha3 exist in same protein complex and that ouabain in nanomolar concentration consistently reduces the calcium response to NMDA. Downregulation of the NMDA response is not associated with internalization of the receptor or with alterations in its state of Src phosphorylation. Ouabain in nanomolar concentration elicits a long-term potentiation response. Our findings suggest that ouabain binding to a fraction of Na,K-ATPase molecules that cluster with the NMDA receptors will, via a conformational effect on the NMDA receptors, cause moderate but consistent reduction of NMDA receptor response at synaptic activation.