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Biological processes are inherently continuous, and the chance of phenotypic discovery is significantly restricted by discretising them. Using multi-parametric active regression we introduce the Regression Plane (RP), a user-friendly discovery tool enabling class-free phenotypic supervised machine learning, to describe and explore biological data in a continuous manner. First, we compare traditional classification with regression in a simulated experimental setup. Second, we use our framework to identify genes involved in regulating triglyceride levels in human cells. Subsequently, we analyse a time-lapse dataset on mitosis to demonstrate that the proposed methodology is capable of modelling complex processes at infinite resolution. Finally, we show that hemocyte differentiation in Drosophila melanogaster has continuous characteristics., High-content screening prompted the development of software enabling discrete phenotypic analysis of single cells. Here, the authors show that supervised continuous machine learning can drive novel discoveries in diverse imaging experiments and present the Regression Plane module of Advanced Cell Classifier.

Aim: Obstructive sleep apnea (OSA) activates the complement system; however, the levels of membrane attack complex (MAC) are unaltered suggesting regulatory mechanisms. Our aim was to investigate complement factor H (CFH) and clusterin, two important complement regulators in OSA. Materials & methods: We analyzed clusterin and CFH levels in plasma of 86 patients with OSA and 33 control subjects. Results: There was no difference in CFH levels between patients (1099.4/784.6–1570.5/μg/ml) and controls (1051.4/652.0–1615.1/μg/ml, p = 0.72). Clusterin levels were higher in patients with OSA (309.7/217.2–763.2/μg/ml vs 276.1/131.0–424.3/μg/ml, p = 0.048) with a trend for a positive correlation with disease severity (p = 0.073). Conclusion: Increase in clusterin levels may be protective in OSA by blocking the MAC formation.

Traumatic brain injury (TBI) was shown to lead to the development of cerebral microbleeds (CMBs), which are associated with long term cognitive decline and gait disturbances in patients. The elderly is one of the most vulnerable parts of the population to suffer TBI. Importantly, ageing is known to exacerbate microvascular fragility and to promote the formation of CMBs. In this overview, the effect of ageing is discussed on the development and characteristics of TBI-related CMBs, with special emphasis on CMBs associated with mild TBI. Four cases of TBI-related CMBs are described to illustrate the concept that ageing exacerbates the deleterious microvascular effects of TBI and that similar brain trauma may induce more CMBs in old patients than in young ones. Recommendations are made for future prospective studies to establish the mechanistic effects of ageing on the formation of CMBs after TBI, and to determine long-term consequences of CMBs on clinically relevant outcome measures including cognitive performance, gait and balance function.

Background Vitamin D metabolism and obesity have been linked by several studies, however the reason for this association is unclear. Our objective was to investigate potential correlations between genetic variants in key enzymes of vitamin D metabolism and the body mass index on a representative and random sample of Hungarian adults. Methods Altogether 462 severely vitamin D deficient individuals were studied at the end of winter in order to decrease environmental and maximize any relevant genetic effect. Furthermore, participants with lifestyle factors known to affect vitamin D homeostasis were also excluded. We selected 23 target SNPs in five genes that encode key proteins of vitamin D metabolism (NADSYN1, GC, CYP24A1, CYP2R1, VDR). Results Variants in 2 genetic polymorphisms; rs2853564 (VDR) and rs11023374 (CYP2R1) showed a significant association with participants‘ BMI. These associations survived further adjustment for total-, free-, or bioactive-25(OH) vitamin D levels, although the variance explained by these 2 SNPS in BMI heterogeneity was only 3.2%. Conclusion Our results show two novel examples of the relationship between genetics of vitamin D and BMI, highlighting the potential role of vitamin D hormone in the physiology of obesity.

Radiation-induced heart disease (RIHD) is a potential late side-effect of thoracic radiotherapy resulting in left ventricular hypertrophy (LVH) and fibrosis due to a complex pathomechanism leading to heart failure. Angiotensin-II receptor blockers (ARBs), including losartan, are frequently used to control heart failure of various etiologies. Preclinical evidence is lacking on the anti-remodeling effects of ARBs in RIHD, while the results of clinical studies are controversial. We aimed at investigating the effects of losartan in a rat model of RIHD. Male Sprague-Dawley rats were studied in three groups: (1) control, (2) radiotherapy (RT) only, (3) RT treated with losartan (per os 10 mg/kg/day), and were followed for 1, 3, or 15 weeks. At 15 weeks post-irradiation, losartan alleviated the echocardiographic and histological signs of LVH and fibrosis and reduced the overexpression of chymase, connective tissue growth factor, and transforming growth factor-beta in the myocardium measured by qPCR; likewise, the level of the SMAD2/3 protein determined by Western blot decreased. In both RT groups, the pro-survival phospho-AKT/AKT and the phospho-ERK1,2/ERK1,2 ratios were increased at week 15. The antiremodeling effects of losartan seem to be associated with the repression of chymase and several elements of the TGF-β/SMAD signaling pathway in our RIHD model.

Proteins are prone to aggregate when they are expressed above their solubility limits, a phenomenon termed supersaturation. Aggregation may occur as proteins emerge from the ribosome or after they fold and accumulate in the cell, but the relative importance of these two routes remain poorly known. Here, we systematically probed the solubility limits of each Escherichia coli protein upon overexpression using an image-based screen coupled with machine learning. The analysis suggests that competition between folding and aggregation from the unfolded state governs the two aggregation routes. Remarkably, the majority (70%) of insoluble proteins have low supersaturation risks in their unfolded states and rather aggregate after folding. Furthermore, a substantial fraction (∼35%) of the proteome remain soluble at concentrations much higher than those found naturally, indicating a large margin of safety to tolerate gene expression changes. We show that high disorder content and low surface stickiness are major determinants of high solubility and are favored in abundant bacterial proteins. Overall, our proteome-wide study provides empirical insights into the molecular determinants of protein aggregation routes in a bacterial cell.

Uremic cardiomyopathy is characterized by diastolic dysfunction (DD), left ventricular hypertrophy (LVH), and fibrosis. Angiotensin-II plays a major role in the development of uremic cardiomyopathy via nitro-oxidative and inflammatory mechanisms. In heart failure, the beta-3 adrenergic receptor (β3-AR) is up-regulated and coupled to endothelial nitric oxide synthase (eNOS)-mediated pathways, exerting antiremodeling effects. We aimed to compare the antiremodeling effects of the angiotensin-II receptor blocker losartan and the β3-AR agonist mirabegron in uremic cardiomyopathy. Chronic kidney disease (CKD) was induced by 5/6th nephrectomy in male Wistar rats. Five weeks later, rats were randomized into four groups: (1) sham-operated, (2) CKD, (3) losartan-treated (10 mg/kg/day) CKD, and (4) mirabegron-treated (10 mg/kg/day) CKD groups. At week 13, echocardiographic, histologic, laboratory, qRT-PCR, and Western blot measurements proved the development of uremic cardiomyopathy with DD, LVH, fibrosis, inflammation, and reduced eNOS levels, which were significantly ameliorated by losartan. However, mirabegron showed a tendency to decrease DD and fibrosis; but eNOS expression remained reduced. In uremic cardiomyopathy, β3-AR, sarcoplasmic reticulum ATPase (SERCA), and phospholamban levels did not change irrespective of treatments. Mirabegron reduced the angiotensin-II receptor 1 expression in uremic cardiomyopathy that might explain its mild antiremodeling effects despite the unchanged expression of the β3-AR.

Graphical abstract, Today, we are fully immersed into the era of 3D biology. It has been extensively demonstrated that 3D models: (a) better mimic the physiology of human tissues; (b) can effectively replace animal models; (c) often provide more reliable results than 2D ones. Accordingly, anti-cancer drug screenings and toxicology studies based on multicellular 3D biological models, the so-called “-oids” (e.g. spheroids, tumoroids, organoids), are blooming in the literature. However, the complex nature of these systems limit the manual quantitative analyses of single cells’ behaviour in the culture. Accordingly, the demand for advanced software tools that are able to perform phenotypic analysis is fundamental. In this work, we describe the freely accessible tools that are currently available for biologists and researchers interested in analysing the effects of drugs/treatments on 3D multicellular -oids at a single-cell resolution level. In addition, using publicly available nuclear stained datasets we quantitatively compare the segmentation performance of 9 specific tools.

Recent statistics report that more than 3.7 million new cases of cancer occur in Europe yearly, and the disease accounts for approximately 20% of all deaths. High-throughput screening of cancer cell cultures has dominated the search for novel, effective anticancer therapies in the past decades. Recently, functional assays with patient-derived ex vivo 3D cell culture have gained importance for drug discovery and precision medicine. We recently evaluated the major advancements and needs for the 3D cell culture screening, and concluded that strictly standardized and robust sample preparation is the most desired development. Here we propose an artificial intelligence-guided low-cost 3D cell culture delivery system. It consists of a light microscope, a micromanipulator, a syringe pump, and a controller computer. The system performs morphology-based feature analysis on spheroids and can select uniform sized or shaped spheroids to transfer them between various sample holders. It can select the samples from standard sample holders, including Petri dishes and microwell plates, and then transfer them to a variety of holders up to 384 well plates. The device performs reliable semi- and fully automated spheroid transfer. This results in highly controlled experimental conditions and eliminates non-trivial side effects of sample variability that is a key aspect towards next-generation precision medicine.

Publisher Copyright: Copyright © 2021 Horváth et al. Oral epithelial cells monitor microbiome composition and initiate immune response upon dysbiosis, as in the case of Candida imbalances. Candida species, such as C. albicans and C. parapsilosis, are the most prevalent yeasts in the oral cavity. Comparison of healthy oral epithelial cell responses revealed that while C. albicans infection robustly activated inflammation cascades, C. parapsilosis primarily activated various inflammation-independent pathways. In posttranscriptional regulatory processes, several miRNAs were altered by both species. For C. parapsilosis, the dose of yeast cells directly correlated with changes in transcriptomic responses with higher fungal burdens inducing significantly different and broader changes. MicroRNAs (miRNAs) associated with carbohydrate metabolism-, hypoxia-, and vascular development-related responses dominated with C. parapsilosis infection, whereas C. albicans altered miRNAs linked to inflammatory responses. Subsequent analyses of hypoxia-inducible factor 1a (HIF1-a) and hepatic stellate cell (HSC) activation pathways predicted target genes through which miRNA-dependent regulation of yeast-specific functions may occur, which also supported the observed species-specific responses. Our findings suggest that C. parapsilosis is recognized as a commensal at low doses by the oral epithelium; however, increased fungal burden activates different pathways, some of which overlap with the inflammatory processes robustly induced by C. albicans. IMPORTANCE A relatively new topic within the field of immunology involves the role of miRNAs in innate as well as adaptive immune response regulation. In recent years, posttranscriptional regulation of host-pathogenic fungal interactions through miRNAs was also suggested. Our study reveals that the distinct nature of human oral epithelial cell responses toward C. parapsilosis and C. albicans is possibly due to species-specific fine-tuning of host miRNA regulatory processes. The findings of this study also shed new light on the nature of early host cell transcriptional responses to the presence of C. parapsilosis and highlight the species’ potential inflammation-independent host activation processes. These findings contribute to our better understanding of how miRNA deregulation at the oral immunological barrier, in non-canonical immune cells, may discriminate between fungal species, particularly Candida species with high or low pathogenic potential.

The formation of Pseudomonas aeruginosa biofilms in cystic fibrosis (CF) is one of the most common causes of morbidity and mortality in CF patients. Cyclic di-GMP and cyclic AMP are second messengers regulating the bacterial lifestyle transition in response to environmental signals. We aimed to investigate the effects of extracellular pH and bicarbonate on intracellular c-di-GMP and cAMP levels, and on biofilm formation. P. aeruginosa was inoculated in a brain–heart infusion medium supplemented with 25 and 50 mM NaCl in ambient air (pH adjusted to 7.4 and 7.7 respectively), or with 25 and 50 mM NaHCO3 in 5% CO2 (pH 7.4 and 7.7). After 16 h incubation, c-di-GMP and cAMP were extracted and their concentrations determined. Biofilm formation was investigated using an xCelligence real-time cell analyzer and by crystal violet assay. Our results show that HCO3− exposure decreased c-di-GMP and increased cAMP levels in a dose-dependent manner. Biofilm formation was also reduced after 48 h exposure to HCO3−. The reciprocal changes in second messenger concentrations were not influenced by changes in medium pH or osmolality. These findings indicate that HCO3−&nbsp, per se modulates the levels of c-di-GMP and cAMP, thereby inhibiting biofilm formation and promoting the planktonic lifestyle of the bacteria.

Nowadays, three dimensional (3D) cell cultures are widely used in the biological laboratories and several optical clearing approaches have been proposed to visualize individual cells in the deepest layers of cancer multicellular spheroids. However, defining the most appropriate clearing approach for the different cell lines is an open issue due to the lack of a gold standard quantitative metric. In this article, we describe and share a single-cell resolution 3D image dataset of human carcinoma spheroids imaged using a light-sheet fluorescence microscope. The dataset contains 90 multicellular cancer spheroids derived from 3 cell lines (i.e. T-47D, 5-8F, and Huh-7D12) and cleared with 5 different protocols, precisely Clear(T) , Clear(T2) , CUBIC, ScaleA2, and Sucrose. To evaluate image quality and light penetration depth of the cleared 3D samples, all the spheroids have been imaged under the same experimental conditions, labelling the nuclei with the DRAQ(5) stain and using a Leica SP8 Digital LightSheet microscope. The clearing quality of this dataset was annotated by 10 independent experts and thus allows microscopy users to qualitatively compare the effects of different optical clearing protocols on different cell lines. It is also an optimal testbed to quantitatively assess different com putational metrics evaluating the image quality in the deepest layers of the spheroids. (C) 2021 The Author(s). Published by Elsevier Inc.

Germline mutations in the BRCA1 and BRCA2 genes are responsible for hereditary breast and ovarian cancer syndrome. Germline and somatic BRCA1/2 mutations may define therapeutic targets and refine cancer treatment options. However, routine BRCA diagnostic approaches cannot reveal the exact time and origin of BRCA1/2 mutation formation, and thus, the fine details of their contribution to tumor progression remain less clear. Here, we establish a diagnostic pipeline using high-resolution microscopy and laser microcapture microscopy to test for BRCA1/2 mutations in the tumor at the single-cell level, followed by deep next-generation sequencing of various tissues from the patient. To demonstrate the power of our approach, here, we describe a detailed single-cell-level analysis of an ovarian cancer patient we found to exhibit constitutional somatic mosaicism of a pathogenic BRCA2 mutation. Employing next-generation sequencing, BRCA2 c.7795G&gt, T, p.(Glu2599Ter) was detected in 78% of reads in DNA extracted from ovarian cancer tissue and 25% of reads in DNA derived from peripheral blood, which differs significantly from the expected 50% of a hereditary mutation. The BRCA2 mutation was subsequently observed at 17–20% levels in the normal ovarian and buccal tissue of the patient. Together, our findings suggest that this mutation occurred early in embryonic development. Characterization of the mosaic mutation at the single-cell level contributes to a better understanding of BRCA mutation formation and supports the concept that the combination of single-cell and next-generation sequencing methods is advantageous over traditional mutational analysis methods. This study is the first to characterize constitutional mosaicism down to the single-cell level, and it demonstrates that BRCA2 mosaicism occurring early during embryogenesis can drive tumorigenesis in ovarian cancer.

Highlights • The primary and secondary structure of lactase was not changed by thermal stress. • The glycan structure of lactase showed significant alterations after heat stress. • Changes in the glycosylation structure affected physico-chemical properties of lactase., Thermal stability of lactase (β-galactosidase) enzyme has been studied by a variety of physico-chemical methods. β-galactosidase is the main active ingredient of medications for lactose intolerance. It is typically produced industrially by the Aspergillus oryzae filamentous fungus. Lactase was used as a model to help understand thermal stability of enzyme-type biopharmaceuticals. Enzyme activity (hydrolyzation of lactose) of β-galactosidase was determined after storing the solid enzyme substance at various temperatures. For a better understanding of the relationship between structure and activity changes we determined the mass and size of the molecules with gel electrophoresis and dynamic light scattering and detected aggregation processes. A bottom-up proteomic procedure was used to determine the primary amino acid sequence and to investigate changes in the N-glycosylation pattern of the protein. NMR and CD spectroscopic methods were used to observe changes in higher order structures and to reveal relationships between structural and functional changes.

The survivin protein contributes to the development and progression of tumors. Protein expression and mRNA levels correlate with clinicopathological parameters and survival of cancer patients. Our purpose was to evaluate whether circulating survivin levels have any diagnostic or predictive value in lung cancer. 118 patients with advanced stage lung cancer participated in our study. 53 suffered from adenocarcinoma (ADC), 33 from squamous cell carcinoma (SqCC), and 32 from small cell lung cancer (SCLC). We also enrolled 21 control subjects. Blood samples were collected before and after two cycles of chemotherapy. We measured survivin concentrations with ELISA. Non-parametric tests were used for analysis. We did not find significant difference in survivin levels between patients and control subjects (17.19/0–829.74/vs. 49.13/0–165.92/pg/ml; p = 0.07). We found lower survivin concentrations in patients with SqCC (0/0–171.24/pg/ml) than in those with ADC (24.94/0–626.46 pg/ml) and SCLC (45.51/0–829.74/pg/ml) (ADC vs. SqCC p < 0.0001, ADC vs. SCLC p = 0.0405, SqCC vs. SCLC p < 0.0001). Survivin levels were higher in stage IV patients than in patients without distant metastases (p = 0.0061), and concentrations were progressively higher with increasing number of metastatic organ sites (p = 0.04). We observed a decrease in survivin levels in ADC patients after platinum plus pemetrexed chemotherapy (26.22/0–626.46/pg/ml before vs. 0/0–114.36/pg/ml after; p = 0.01). Neither progression-free nor overall survival correlated with survivin levels at baseline. Our data imply that survivin may be involved in the development of metastases and it might be used as a biomarker of disease progression. However, circulating survivin concentrations do not predict survival of patients with lung cancer.

SummarySystematic insight into cellular dysfunctions can improve understanding of disease etiology, risk assessment and patient stratification. We present a multiparametric high-content imaging platform enabling quantification of low-density lipoprotein (LDL) uptake and lipid storage in cytoplasmic droplets of primary leukocyte subpopulations. We validated this platform with samples from 65 individuals with variable blood LDL-cholesterol (LDL-c) levels, including familial hypercholesterolemia (FH) and non-FH subjects. We integrated lipid storage data into a novel readout, lipid mobilization, measuring the efficiency with which cells deplete lipid reservoirs. Lipid mobilization correlated positively with LDL uptake and negatively with hypercholesterolemia and age, improving differentiation of individuals with normal and elevated LDL-c. Moreover, combination of cell-based readouts with a polygenic risk score for LDL-c explained hypercholesterolemia better than the genetic risk score alone. This platform provides functional insights into cellular lipid trafficking from a few ml’s of blood and is applicable to dissect metabolic disorders, such as hypercholesterolemia.MotivationWe have limited information on how cellular lipid uptake and processing differ between individuals and influence the development of metabolic diseases, such as hypercholesterolemia. Available assays are labor intensive, require skilled personnel and are difficult to scale to higher throughput, making it challenging to obtain systematic functional cell-based data from individuals. To overcome this problem, we established a scalable automated analysis pipeline enabling reliable quantification of multiple cellular readouts, including lipid uptake, storage and mobilization, from different white blood cell populations. This approach provides new personalized insights into the cellular basis of hypercholesterolemia and obesity.Graphical Abstract

Patch clamp recording of neurons is a labor-intensive and time-consuming procedure. Here, we demonstrate a tool that fully automatically performs electrophysiological recordings in label-free tissue slices. The automation covers the detection of cells in label-free images, calibration of the micropipette movement, approach to the cell with the pipette, formation of the whole-cell configuration, and recording. The cell detection is based on deep learning. The model is trained on a new image database of neurons in unlabeled brain tissue slices. The pipette tip detection and approaching phase use image analysis techniques for precise movements. High-quality measurements are performed on hundreds of human and rodent neurons. We also demonstrate that further molecular and anatomical analysis can be performed on the recorded cells. The software has a diary module that automatically logs patch clamp events. Our tool can multiply the number of daily measurements to help brain research., Patch clamp recording of neurons is slow and labor-intensive. Here the authors present a method for automated deep learning driven label-free image guided patch clamp physiology to perform measurements on hundreds of human and rodent neurons.

Oral epithelial cells monitor microbiome composition and initiate immune response upon dysbiosis, as in case of Candida imbalances. Comparison of healthy oral epithelial cell responses revealed that the inability of C. parapsilosis to induce a robust antifungal response was due to activation of various inflammation-independent pathways, while C. albicans robustly activated inflammation cascades. Regarding posttranscriptional regulation, several miRNAs were altered by both species. For C. parapsilosis, the applied dose directly correlated with changes in transcriptomic responses. Carbohydrate metabolism, hypoxia- and cardiovascular development-related responses dominate after C. parapsilosis stimulus, whereas C. albicans altered inflammatory responses. Subsequent analyses of HIF1-α and HSC-activation pathways predicted target genes through which miRNA-dependent regulation of yeast-specific functions may occur, supporting the observed responses. Thus, C. parapsilosis is recognized as a commensal at low doses by the oral epithelium; however, increased fungal burden activates different pathways, some of which overlap with inflammatory processes induced by C. albicans.Impact statementAltered miRNA regulation discriminates between C. albicans and C. parapsilosis in human oral epithelial cells

Simple Summary The conventional central nervous system (CNS) tumor diagnostic methods, especially the invasive intracranial surgical tissue sample collecting, imposes a heavy burden on both patients and healthcare providers. We aimed to explore the potential role of serum-derived small extracellular vesicles (sEVs) in diagnosing CNS tumors through Raman spectroscopic analyses. A relevant number of clinical samples (138) were obtained from four patient groups, namely glioblastoma multiforme, brain metastasis of non-small-cell lung cancer, meningioma, and lumbar disc herniation as controls. After the isolation and Raman measurements of sEV-sized particles, the Principal Component Analysis–Support Vector Machine algorithm was performed on the Raman spectra for pairwise classifications. The groups compared were distinguishable with 80–95% sensitivity and 80–90% specificity. Our results support that Raman spectroscopic analysis of sEV-sized particles is a promising liquid-biopsy-based method that could be further developed in order to be applicable in the diagnosis of CNS tumors. Abstract Investigating the molecular composition of small extracellular vesicles (sEVs) for tumor diagnostic purposes is becoming increasingly popular, especially for diseases for which diagnosis is challenging, such as central nervous system (CNS) malignancies. Thorough examination of the molecular content of sEVs by Raman spectroscopy is a promising but hitherto barely explored approach for these tumor types. We attempt to reveal the potential role of serum-derived sEVs in diagnosing CNS tumors through Raman spectroscopic analyses using a relevant number of clinical samples. A total of 138 serum samples were obtained from four patient groups (glioblastoma multiforme, non-small-cell lung cancer brain metastasis, meningioma and lumbar disc herniation as control). After isolation, characterization and Raman spectroscopic assessment of sEVs, the Principal Component Analysis–Support Vector Machine (PCA–SVM) algorithm was performed on the Raman spectra for pairwise classifications. Classification accuracy (CA), sensitivity, specificity and the Area Under the Curve (AUC) value derived from Receiver Operating Characteristic (ROC) analyses were used to evaluate the performance of classification. The groups compared were distinguishable with 82.9–92.5% CA, 80–95% sensitivity and 80–90% specificity. AUC scores in the range of 0.82–0.9 suggest excellent and outstanding classification performance. Our results support that Raman spectroscopic analysis of sEV-enriched isolates from serum is a promising method that could be further developed in order to be applicable in the diagnosis of CNS tumors.

State-dependent thalamocortical activity is important for sensory coding, oscillations, and cognition. The lateral geniculate nucleus (LGN) relays visual information to the cortex, but the state-dependent spontaneous activity of LGN neurons in awake behaving animals remains controversial. Using a combination of pupillometry, extracellular, and intracellular recordings from identified LGN neurons in behaving mice, we show that thalamocortical (TC) neurons and interneurons are distinctly correlated to arousal forming two complementary coalitions. Intracellular recordings indicated that the membrane potential of LGN TC neurons was tightly correlated to fluctuations in pupil size. Inactivating the corticothalamic feedback to the LGN suppressed the arousal dependency of LGN neurons. Taken together, our results show that LGN neuronal membrane potential and action potential output are dynamically linked to arousal-dependent brain states in awake mice, and this might have important functional implications.

Graphical abstract, 3D multicellular spheroids quickly emerged as in vitro models because they represent the in vivo tumor environment better than standard 2D cell cultures. However, with current microscopy technologies, it is difficult to visualize individual cells in the deeper layers of 3D samples mainly because of limited light penetration and scattering. To overcome this problem several optical clearing methods have been proposed but defining the most appropriate clearing approach is an open issue due to the lack of a gold standard metric. Here, we propose a guideline for 3D light microscopy imaging to achieve single-cell resolution. The guideline includes a validation experiment focusing on five optical clearing protocols. We review and compare seven quality metrics which quantitatively characterize the imaging quality of spheroids. As a test environment, we have created and shared a large 3D dataset including approximately hundred fluorescently stained and optically cleared spheroids. Based on the results we introduce the use of a novel quality metric as a promising method to serve as a gold standard, applicable to compare optical clearing protocols, and decide on the most suitable one for a particular experiment.

The volume is one of the most relevant features that define the treatment of an in vivo tumour. When using cancer 3D in vitro models in pre-clinical studies, it becomes important to evaluate the macroscopic effects of drugs and radiotherapy treatments. Depending on the nature of the 3D in vitro model used, different open-source solutions can be used for measuring the volume by starting from microscope-acquired images. In this work, we introduced several open-source tools today available for estimating the volume of 3D multicellular aggregates (e.g., spheroids, organoids), also giving hints for defining the &ldquo, best software&rdquo, by analysing characteristics of 3D in vitro models and limits of the tools. Finally, using several cancer organoids imaged by a fluorescent microscope, we compared volume estimations obtained with different tools, besides presenting a new version of the Reconstruction and Visualization from Multiple Sections (ReViMS version 2.0) tool. This work aims to be the reference for researchers interested in estimating the volume of 3D multicellular aggregates through an open-source tool.

Another host factor for SARS-CoV-2 Virus-host interactions determine cellular entry and spreading in tissues. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and the earlier SARS-CoV use angiotensin-converting enzyme 2 (ACE2) as a receptor; however, their tissue tropism differs, raising the possibility that additional host factors are involved. The spike protein of SARS-CoV-2 contains a cleavage site for the protease furin that is absent from SARS-CoV (see the Perspective by Kielian). Cantuti-Castelvetri et al. now show that neuropilin-1 (NRP1), which is known to bind furin-cleaved substrates, potentiates SARS-CoV-2 infectivity. NRP1 is abundantly expressed in the respiratory and olfactory epithelium, with highest expression in endothelial and epithelial cells. Daly et al. found that the furin-cleaved S1 fragment of the spike protein binds directly to cell surface NRP1 and blocking this interaction with a small-molecule inhibitor or monoclonal antibodies reduced viral infection in cell culture. Understanding the role of NRP1 in SARS-CoV-2 infection may suggest potential targets for future antiviral therapeutics. Science , this issue p. 856 , p. 861 ; see also p. 765

Efficient cell migration requires cellular polarization, which is characterized by the formation of leading and trailing edges, appropriate positioning of the nucleus and reorientation of the Golgi apparatus and centrosomes toward the leading edge. Migration also requires the development of an asymmetrical front-to-rear calcium (Ca2+) gradient to regulate focal adhesion assembly and actomyosin contractility. Here we demonstrate that silencing of syndecan-4, a transmembrane heparan sulfate proteoglycan, interferes with the correct polarization of migrating mammalian myoblasts (i.e., activated satellite stem cells). In particular, syndecan-4 knockdown completely abolished the intracellular Ca2+ gradient, abrogated centrosome reorientation and thus decreased cell motility, demonstrating the role of syndecan-4 in cell polarity. Additionally, syndecan-4 exhibited a polarized distribution during migration. Syndecan-4 knockdown cells exhibited decreases in the total movement distance during directional migration, maximum and vectorial distances from the starting point, as well as average and maximum cell speeds. Super-resolution direct stochastic optical reconstruction microscopy images of syndecan-4 knockdown cells revealed nanoscale changes in the actin cytoskeletal architecture, such as decreases in the numbers of branches and individual branch lengths in the lamellipodia of the migrating cells. Given the crucial importance of myoblast migration during embryonic development and postnatal muscle regeneration, we conclude that our results could facilitate an understanding of these processes and the general role of syndecan-4 during cell migration.

AnnotatorJ combines single-cell identification with deep learning (DL) and manual annotation. Cellular analysis quality depends on accurate and reliable detection and segmentation of cells so that the subsequent steps of analyses, for example, expression measurements, may be carried out precisely and without bias. DL has recently become a popular way of segmenting cells, performing unimaginably better than conventional methods. However, such DL applications may be trained on a large amount of annotated data to be able to match the highest expectations. High-quality annotations are unfortunately expensive as they require field experts to create them, and often cannot be shared outside the lab due to medical regulations. We propose AnnotatorJ, an ImageJ plugin for the semiautomatic annotation of cells (or generally, objects of interest) on (not only) microscopy images in 2D that helps find the true contour of individual objects by applying U-Net-based presegmentation. The manual labor of hand annotating cells can be significantly accelerated by using our tool. Thus, it enables users to create such datasets that could potentially increase the accuracy of state-of-the-art solutions, DL or otherwise, when used as training data.

Biological processes are inherently continuous, and the chance of phenotypic discovery is significantly restricted by discretising them. Using multi-parametric active regression we introduce a novel concept to describe and explore biological data in a continuous manner. We have implementedRegression Plane (RP), the first user-friendly discovery tool enabling class-free phenotypic supervised machine learning.

SARS-CoV-2 is the causative agent of COVID-19, a coronavirus disease that has infected more than 6.6 million people and caused over 390,000 deaths worldwide1,2. The Spike (S) protein of the virus forms projections on the virion surface responsible for host cell attachment and penetration. This viral glycoprotein is synthesized as a precursor in infected cells and, to be active, must be cleaved to two associated polypeptides: S1 and S2(3,4). For SARS-CoV-2 the cleavage is catalysed by furin, a host cell protease, which cleaves the S protein precursor at a specific sequence motif that generates a polybasic Arg-Arg-Ala-Arg (RRAR) C-terminal sequence on S1. This sequence motif conforms to the C-end rule (CendR), which means that the C-terminal sequence may allow the protein to associate with cell surface neuropilin-1 (NRP1) and neuropilin-2 (NRP2) receptors5. Here we demonstrate using immunoprecipitation, site-specific mutagenesis, structural modelling, and antibody blockade that, in addition to engaging the known receptor ACE2, S1 can bind to NRP1 through the canonical CendR mechanism. This interaction enhances infection by SARS-CoV-2 in cell culture. NRP1 thus serves as a host factor for SARS-CoV-2 infection, and provides a therapeutic target for COVID-19.

Patch clamp recording of neurons is a labor-intensive and time-consuming procedure. We have developed a tool that fully automatically performs electrophysiological recordings in label-free tissue slices. The automation covers the detection of cells in label-free images, calibration of the micropipette movement, approach to the cell with the pipette, formation of the whole-cell configuration, and recording. The cell detection is based on deep learning. The model was trained on a new image database of neurons in unlabeled brain tissue slices. The pipette tip detection and approaching phase use image analysis techniques for precise movements. High-quality measurements were performed on hundreds of human and rodent neurons. We also demonstrate that further molecular and anatomical analysis can be performed on the recorded cells. The software has a diary module that automatically logs patch clamp events. Our tool can multiply the number of daily measurements to help brain research.ONE SENTENCE SUMMARYNovel deep learning and image analysis algorithms for automated patch clamp systems to reliably measure neurons in human and rodent brain slices.

Recent advancements in deep learning have revolutionized the way microscopy images of cells are processed. Deep learning network architectures have a large number of parameters, thus, in order to reach high accuracy, they require a massive amount of annotated data. A common way of improving accuracy builds on the artificial increase of the training set by using different augmentation techniques. A less common way relies on test-time augmentation (TTA) which yields transformed versions of the image for prediction and the results are merged. In this paper we describe how we have incorporated the test-time argumentation prediction method into two major segmentation approaches utilized in the single-cell analysis of microscopy images. These approaches are semantic segmentation based on the U-Net, and instance segmentation based on the Mask R-CNN models. Our findings show that even if only simple test-time augmentations (such as rotation or flipping and proper merging methods) are applied, TTA can significantly improve prediction accuracy. We have utilized images of tissue and cell cultures from the Data Science Bowl (DSB) 2018 nuclei segmentation competition and other sources. Additionally, boosting the highest-scoring method of the DSB with TTA, we could further improve prediction accuracy, and our method has reached an ever-best score at the DSB.

Exquisite regulation of PI3K/AKT/mTORC1 signaling is essential for homeostatic control of cell growth, proliferation, and survival. Aberrant activation of this signaling network is an early driver of many sporadic human cancers. Paradoxically, sustained hyperactivation of the PI3K/AKT/mTORC1 pathway in nontransformed cells results in cellular senescence, which is a tumor-suppressive mechanism that must be overcome to promote malignant transformation. While oncogene-induced senescence (OIS) driven by excessive RAS/ERK signaling has been well studied, little is known about the mechanisms underpinning the AKT-induced senescence (AIS) response. Here, we utilize a combination of transcriptome and metabolic profiling to identify key signatures required to maintain AIS. We also employ a whole protein-coding genome RNAi screen for AIS escape, validating a subset of novel mediators and demonstrating their preferential specificity for AIS as compared with OIS. As proof of concept of the potential to exploit the AIS network, we show that neurofibromin 1 (NF1) is upregulated during AIS and its ability to suppress RAS/ERK signaling facilitates AIS maintenance. Furthermore, depletion of NF1 enhances transformation of p53-mutant epithelial cells expressing activated AKT, while its overexpression blocks transformation by inducing a senescent-like phenotype. Together, our findings reveal novel mechanistic insights into the control of AIS and identify putative senescence regulators that can potentially be targeted, with implications for new therapeutic options to treat PI3K/AKT/mTORC1-driven cancers.

Segmentation of objects with known geometries in an image is a fundamental research problem. In this paper we show a three-dimensional energy minimization model to detect the tip of glass micropipettes in fluorescence microscopy image stacks. The described model fits a truncated cone to the bright intensities in the image. The model is minimized using gradient descent. The number of parameters is fairly low to achieve fast evolution and noise insensitivity. The algorithm is tested on fluorescence microscopy image stacks. The error of the tip detection is only a few micrometers. Automatic pipette tip detection is a step forward to automate the patch clamp process, used for recording the electrophysiological properties of living neurons or myocytes. The described method can easily be extended to other applications or find multiple objects with a connection, e.g., lines for road intersection detection.

Extended nitric oxide (NO) analysis offers the partitioned monitoring of inflammation in central and peripheral airways. Different mathematical models are used to estimate pulmonary NO dynamics in asthma with variable results and limitations. We aimed to establish a protocol for extended NO analysis in patients with differing asthma severity.Forty patients with stable asthma and 25 matched control subjects were recruited. Exhaled NO was measured at constant flow rates between 10 and 300 mL/s. Twelve controls performed NO measurements weekly for 4 weeks.The proportions of patients with technically acceptable measurements at 10-30-50-100-150-200-250-300 mL/s exhalation flow rates were 8-58-100-98-98-95-90-80%, respectively. Alveolar NO (CANO) and total flux of NO in the conducting airways (JawNO) were calculated with the linear method from NO values measured at 100-150-200-250 mL/s exhalation flows. The mean intrasubject bias for JawNO and CANO in controls was 0.16 nL/s and 0.85 ppb, respectively. Both JawNO (1.31/0.83-2.97/vs. 0.70/0.54-0.87/nL/s, p 0.001) and CANO (4.08/2.63-7.16/vs. 2.42/1.83-2.89/ppb, p 0.001) were increased in patients with asthma compared to controls. In patients, CANO correlated with RV/TLC (r = 0.58, p 0.001), FEFCalculation of alveolar NO concentration with the linear method from values obtained at medium flow rates (100-250 mL/s) is feasible even in asthmatic patients with severe airflow limitation and may provide information on small airways dysfunction in asthma.

Phenotypic image analysis is the task of recognizing variations in cell properties using microscopic image data. These variations, produced through a complex web of interactions between genes and the environment, may hold the key to uncover important biological phenomena or to understand the response to a drug candidate. Today, phenotypic analysis is rarely performed completely by hand. The abundance of high-dimensional image data produced by modern high-throughput microscopes necessitates computational solutions. Over the past decade, a number of software tools have been developed to address this need. They use statistical learning methods to infer relationships between a cell's phenotype and data from the image. In this review, we examine the strengths and weaknesses of non-commercial phenotypic image analysis software, cover recent developments in the field, identify challenges, and give a perspective on future possibilities. The goal of phenotypic image analysis is to recognize variations in cellular properties using image data—either measurements extracted by image analysis software or directly from the raw pixel values. In this review, we describe free and open-source software tools that are currently available for exploring and quantifying phenotypes in image-based cellular assays. We discuss some of the main challenges, current trends, and future research directions in phenotypic image analysis.

Incubation time plays a critical role in the accurate measurement of equilibrium solubility of compounds. Substances which dissolve very slowly generally need long incubation times (days or weeks) to reach equilibrium. However, long times may pose several problems, such as decomposition of solute, molding of buffer, and drifting of pH. Higuchi in 1979 proposed the Facilitated Dissolution Method (FDM) to dramatically reduce incubation time. It employs a small volume of water-immiscible organic solvent to partly solubilize the sample and thereby increase the surface area available for dissolution. The method has been used only rarely. In this study we performed a systematic validation of FDM using progesterone as model compound. The reference solubility value, 7.95±0.21μg/mL (p0.05, n=5), was determined in Britton-Robinson buffer solution (pH7.4) at 25.0°C by the standardized protocol of Saturation Shake-Flask (SSF) method. Also, the solubility was measured by the FDM approach under varied experimental conditions (e.g., type and volume of organic solvent, time of agitation, and amount of solid excess), and compared to the reference value. It was demonstrated that the small amount of organic solvent used in the FDM does not impact the measured solubility, compared to the reference value. Additionally, four compounds of low dissolution rate (dexamethasone, digoxin, haloperidol and cosalane) were used to demonstrate that FDM can reduce the long equilibration time to the standardized 24h (6h stirring and 18h sedimentation). The time dependence of solubility equilibrium was measured by SSF, and the results were compared with those obtained by FDM. Our study, based on200 solubility experiments, supports the validity of Higuchi's method. In this study we propose a standardized protocol for the FDM, where 1% v/v of organic solvent is used. Octane (or isooctane) was found to be suitable for highly hydrophobic compounds. Alternatively, octanol or 1,2-dichloroethane can be used for less lipophilic compounds.

Traumatic brain injury (TBI) was shown to impair pressure-induced myogenic response of cerebral arteries, which is associated with vascular and neural dysfunction and increased mortality of TBI patients. Hypertension was shown to enhance myogenic tone of cerebral arteries via increased vascular production of 20-hydroxyeicosatrienoic acid (HETE). This adaptive mechanism protects brain tissue from pressure/volume overload; however, it can also lead to increased susceptibility to cerebral ischemia. Although both effects may potentiate the detrimental vascular consequences of TBI, it is not known how hypertension modulates the effect of TBI on myogenic responses of cerebral vessels. We hypothesized that in hypertensive rats, the enhanced myogenic cerebrovascular response is preserved after TBI. Therefore, we investigated the myogenic responses of isolated middle cerebral arteries (MCA) of normotensive and spontaneously hypertensive rats (SHR) after severe impact acceleration diffuse brain injury. TBI diminished myogenic constriction of MCAs isolated from normotensive rats, whereas the 20-HETE-mediated enhanced myogenic response of MCAs isolated from SHRs was not affected by TBI. These results suggest that the optimal cerebral perfusion pressure values and vascular signaling pathways can be different and, therefore, should be targeted differently in normotensive and hypertensive patients following TBI.

Traumatic brain injury (TBI) is recognized to be the main cause of death and disability in the first four decades representing a major socio-economical problem worldwide. Recent communications revealed a particularly worrying image about the quality of care for TBI in Hungary. For any improvement a systematic approach characterized by utilization of scientific evidence based guidelines forming the basis for close monitoring of the actual care are considered a prerequisite. In Hungary the first evidence based guidelines in the field of TBI have been issued by the National Society for Anesthesiology and Intensive Care more than two decades ago followed by joint guidelines of the Hungarian Neurosurgical Society and the Hungarian College of Neurosurgeons. These publications were primarily based on the work of the European Brain Injury Consortium as well as guidelines issued by the Brain Trauma Foundation. Recent renewal of the latter and a need to refresh the outdated national guidelines was met by a call from regulatory authorities to issue the updated version of the Hungarian TBI-guidelines. The present review is aimed to briefly summarize the most fundamental elements of the national head injury guidelines that would hopefully be officially issued in a far more detailed format soon.

To facilitate analysis of spatial tissue phenotypes, we created an open-source tool package named ‘Spa-RQ’ for ‘Spatial tissue analysis: image Registration & Quantification’. Spa-RQ contains software for image registration (Spa-R) and quantitative analysis of DAB staining overlap (Spa-Q). It provides an easy-to-implement workflow for serial sectioning and staining as an alternative to multiplexed techniques. To demonstrate Spa-RQ’s applicability, we analysed the spatial aspects of oncogenic KRAS-related signalling activities in non-small cell lung cancer (NSCLC). Using Spa-R in conjunction with ImageJ/Fiji, we first performed annotation-guided tumour-by-tumour phenotyping using multiple signalling markers. This analysis showed histopathology-selective activation of PI3K/AKT and MAPK signalling in Kras mutant murine tumours, as well as high p38MAPK stress signalling in p53 null murine NSCLC. Subsequently, Spa-RQ was applied to measure the co-activation of MAPK, AKT, and their mutual effector mTOR pathway in individual tumours. Both murine and clinical NSCLC samples could be stratified into ‘MAPK/mTOR’, ‘AKT/mTOR’, and ‘Null’ signature subclasses, suggesting mutually exclusive MAPK and AKT signalling activities. Spa-RQ thus provides a robust and easy to use tool that can be employed to identify spatially-distributed tissue phenotypes.

Recently, it has been described that programmed cell death protein 1 (PD-1) overexpressing melanoma cells are highly aggressive. However, until now it has not been defined which factors lead to the generation of PD-1 overexpressing subpopulations. Here, we present that melanoma-derived exosomes, conveying oncogenic molecular reprogramming, induce the formation of a melanoma-like, PD-1 overexpressing cell population (mMSCPD-1+) from naïve mesenchymal stem cells (MSCs). Exosomes and mMSCPD-1+ cells induce tumor progression and expression of oncogenic factors in vivo. Finally, we revealed a characteristic, tumorigenic signaling network combining the upregulated molecules (e.g., PD-1, MET, RAF1, BCL2, MTOR) and their upstream exosomal regulating proteins and miRNAs. Our study highlights the complexity of exosomal communication during tumor progression and contributes to the detailed understanding of metastatic processes.

Seipin is an oligomeric integral endoplasmic reticulum (ER) protein involved in lipid droplet (LD) biogenesis. To study the role of seipin in LD formation, we relocalized it to the nuclear envelope and found that LDs formed at these new seipin-defined sites. The sites were characterized by uniform seipin-mediated ER-LD necks. At low seipin content, LDs only grew at seipin sites, and tiny, growth-incompetent LDs appeared in a Rab18-dependent manner. When seipin was removed from ER-LD contacts within 1 h, no lipid metabolic defects were observed, but LDs became heterogeneous in size. Studies in seipin-ablated cells and model membranes revealed that this heterogeneity arises via a biophysical ripening process, with triglycerides partitioning from smaller to larger LDs through droplet-bilayer contacts. These results suggest that seipin supports the formation of structurally uniform ER-LD contacts and facilitates the delivery of triglycerides from ER to LDs. This counteracts ripening-induced shrinkage of small LDs.

SummarySegmentation of single cells in microscopy images is one of the major challenges in computational biology. It is the first step of most bioimage analysis tasks, and essential to create training sets for more advanced deep learning approaches. Here, we propose 3D-Cell-Annotator to solve this task using 3D active surfaces together with shape descriptors as prior information in a fully- and semi-automated fashion. The software uses the convenient 3D interface of the widely used Medical Imaging Interaction Toolkit (MITK). Results on 3D biological structures (e.g. spheroids, organoids, embryos) show that the precision of the segmentation reaches the level of a human expert.Availability and implementation3D-Cell-Annotator is implemented in CUDA/C++ as a patch for the segmentation module of MITK. The 3D-Cell-Annotator enabled MITK distribution can be downloaded at:www.3D-cell-annotator.org. It works under Windows 64-bit systems and recent Linux distributions even on a consumer level laptop with a CUDA-enabled video card using recent NVIDIA drivers.Contactsfilippo.piccinini@irst.emr.itandhorvath.peter@brc.mta.hu

BACKGROUND Obstructive sleep apnoea (OSA) is characterised by chronic intermittent hypoxia, which enhances airway inflammation and oxidative stress. Exhaled carbon monoxide (eCO), a marker for oxidative stress, has been investigated in OSA. However, previous studies could be biased as they did not differentiate patients with OSA based on smoking history, a known factor influencing eCO levels. The aim of this study to investigate eCO levels in patients with OSA and non-OSA controls and compare evening to morning results. METHODS Exhaled carbon monoxide concentration was measured in the evening and in the morning following an in-hospital cardiorespiratory polygraphy in 60 never-smoker OSA patients, 14 ex-smoker OSA patients, 39 current-smoker OSA patients, 10 never-smoker asthmatic patients with OSA, 16 COPD patients with OSA and 20 never-smoker non-OSA controls. OSA was diagnosed based on the apnoea-hypopnoea index (AHI > 5/h). RESULTS There was no difference between the never-smoker controls and never-smoker patients with OSA either in the evening (1.98 ± 1.00 ppm versus 1.95 ± 1.28 ppm, p = 0.57, OSA versus controls, respectively) or morning (1.95 ± 0.96 ppm versus 1.80 ± 0.95 ppm, p = 0.42), however there was a weak correlation between eCO and AHI in the evening (r = 0.31, p = 0.01). Accordingly, patients with severe OSA had higher eCO levels in the evening (2.43 ± 1.12 ppm) compared to mild OSA patients (1.57 ± 0.87 ppm, p

Single cell segmentation is typically one of the first and most crucial tasks of image-based cellular analysis. We present a deep learning approach aiming towards a truly general method for localizing nuclei across a diverse range of assays and light microscopy modalities. We outperform the 739 methods submitted to the 2018 Data Science Bowl on images representing a variety of realistic conditions, some of which were not represented in the training data. The key to our approach is to adapt our model to unseen and unlabeled data using image style transfer to generate augmented training samples. This allows the model to recognize nuclei in new and different experiments without requiring expert annotations.

Purpose: Obstructive sleep apnoea (OSA) represents a risk for dyslipidaemia. Obstructive respiratory events during rapid eye movement (REM) sleep are more strongly related to the development of hypertension and diabetes than in non-REM. However, the relationship between sleep phases and serum lipid profile is unclear. We aimed to analyse the relationship between obstructive respiratory events in REM and non-REM sleep as well as serum lipid profile. Methods: Polysomnography was performed in 94 adult subjects who did not take any lipid-modifying medications. Fasting venous blood sample was taken the following morning for total cholesterol, triglyceride, high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol, lipoprotein(a), apoprotein A1 (ApoA1) and for apoprotein B (ApoB) measurements. Lipid profiles were correlated with apnoea–hypopnoea index (AHI) during REM (AHI REM) and non-REM (AHI NREM) stages in all subjects. In addition, lipid profiles were compared between REM-dependent OSA patients (AHI REM ≥ 5/h, but AHI NREM < 5/h) and control subjects (both AHI REM and AHI NREM < 5/h). Results: AHI REM correlated only with triglyceride concentrations (p = 0.04, Spearman’s rho, ρ = 0.21). In contrast, there was a significant association between AHI NREM and triglyceride (p = 0.02, ρ = 0.23), ApoB (p = 0.03, ρ = 0.21), HDL-C (p < 0.01, ρ = − 0.32) as well as ApoA1 levels (p = 0.04, ρ = − 0.21). However, these correlations were not present after adjustment for BMI (all p > 0.05). There was no difference in the lipid profile of REM-dependent OSA subjects and healthy controls (p > 0.05). Conclusions: Altered serum lipid profile is equally associated with a disturbed REM and non-REM sleep in OSA. Obesity must be considered as a strong covariate when interpreting lipid data in sleep apnoea.

Temporal resolution of cellular features associated with a severe COVID-19 disease trajectory is required for understanding skewed immune responses and finding outcome predictors. Here, we performed a longitudinal multi-omics study using a two-centre cohort of 14 patients. We analysed the bulk transcriptome, bulk DNA methylome, and single-cell transcriptome (>358,000 cells, including BCR profiles) of peripheral blood samples harvested from up to 5 time points. Validation was performed in two independent cohorts of COVID-19 patients. Severe COVID-19 was characterized by an increase of proliferating, metabolically hyperactive plasmablasts. Coinciding with critical illness, we also identified an expansion of IFN-activated circulating megakaryocytes and increased erythropoiesis with features of hypoxic signalling. Megakaryocyte- and erythroid cell-derived co-expression modules were predictive of fatal disease outcome. The study demonstrates broad cellular effects of SARS-CoV-2 infection beyond classical immune cells and may serve as an entry point to develop biomarkers and targeted treatments of patients with COVID-19., Graphical Abstract, Highlights • SARS-CoV2 infection elicits dynamic changes of circulating cells in the blood • Severe COVID-19 is characterized by increased metabolically active plasmablasts • Elevation of IFN-activated megakaryocytes and erythroid cells in severe COVID-19 • Cell-type specific expression signatures are associated with a fatal COVID-19 outcome, Bernardes et al. explore COVID-19 disease trajectories by performing longitudinal multi-omics analyses in peripheral blood samples from hospitalized patients. The analyses identify increased numbers of plasmablasts, interferon-activated megakaryocytes and erythroid cells as hallmarks of severe disease, and define molecular signatures linked to a fatal COVID-19 disease outcome.

Tyrosine kinase inhibitors are widely used for treatment of certain oncohematological diseases. Several clinical studies have confirmed that specific BCR-ABL tyrosine kinase inhibitors alter the physiological process of bone tissue in a complex and unclearly identified manner. Since these treatments are being given to more and more patients, and the therapy takes decades or lasts even lifelong, it is justifiable to obtain more detailed knowledge of the molecular background of these mechanisms. In this article the authors summarize preliminary research results and human clinical observations on imatinib and nilotinib which are related to bone metabolism, and present the results of their own experiments in in vitro osteoblast cultures. Based on the presented results, the effects of imatinib and nilotinib on bone cells depend on the concentration of imatinib and nilotinib, the maturation stage of the cells and the distribution ratio of receptor tyrosine kinase signaling pathways. In this study the authors firstly prepared a stop-gap, comprehensive review in the Hungarian literature, regarding the effects of tyrosine kinase inhibitors on bone metabolism. In addition they firstly performed whole transcriptome analysis on osteoblasts in order to obtain a better understanding of the cellular molecular mechanisms. Orv. Hetil., 2016, 157(36), 1429–1437.

Hyperactivation of the PI3K/AKT/mTORC1 signaling pathway is a hallmark of the majority of sporadic human cancers. Paradoxically, chronic activation of this pathway in nontransformed cells promotes senescence, which acts as a significant barrier to malignant progression. Understanding how this oncogene-induced senescence is maintained in nontransformed cells and conversely how it is subverted in cancer cells will provide insight into cancer development and potentially identify novel therapeutic targets. High-throughput screening provides a powerful platform for target discovery. Here, we describe an approach to use RNAi transfection of a pre-established AKT-induced senescent cell population and subsequent high-content imaging to screen for senescence regulators. We have incorporated multiparametric readouts, including cell number, proliferation, and senescence-associated beta-galactosidase (SA-βGal) staining. Using machine learning and automated image analysis, we also describe methods to classify distinct phenotypes of cells with SA-βGal staining. These methods can be readily adaptable to high-throughput functional screens interrogating the mechanisms that maintain and prevent senescence in various contexts.

Objective. Wilson’s disease is a disorder of copper metabolism which is fatal without treatment. The great number of disease-causingATP7Bgene mutations and the variable clinical presentation of WD may cause a real diagnostic challenge. The emergence of next-generation sequencing provides a time-saving, cost-effective method for full sequencing of the wholeATP7Bgene compared to the traditional Sanger sequencing. This is the first report on the clinical use of NGS to examineATP7Bgene.Materials and Methods. We used Ion Torrent Personal Genome Machine in four heterozygous patients for the identification of the other mutations and also in two patients with no known mutation. One patient with acute on chronic liver failure was a candidate for acute liver transplantation. The results were validated by Sanger sequencing.Results. In each case, the diagnosis of Wilson’s disease was confirmed by identifying the mutations in both alleles within 48 hours. One novel mutation (p.Ala1270Ile) was found beyond the eight other known ones. The rapid detection of the mutations made possible the prompt diagnosis of WD in a patient with acute liver failure.Conclusions. According to our results we found next-generation sequencing a very useful, reliable, time-saving, and cost-effective method for diagnosing Wilson’s disease in selected cases.

Ribosome biogenesis is a highly complex process requiring many assisting factors. Studies in yeast have yielded comprehensive knowledge of the cellular machinery involved in this process. However, many aspects of ribosome synthesis are different in higher eukaryotes, and the global set of mammalian ribosome biogenesis factors remains unexplored. We used an imaging-based, genome-wide RNAi screen to find human proteins involved in 40S ribosomal subunit biogenesis. Our analysis identified ∼300 factors, many part of essential protein modules such as the small subunit (SSU) processome, the eIF3 and chaperonin complexes, and the ubiquitin-proteasome system. We demonstrate a role for the vertebrate-specific factor RBIS in ribosome synthesis, uncover a requirement for the CRL4 E3 ubiquitin ligase in nucleolar ribosome biogenesis, and reveal that intracellular glutamine synthesis supports 40S subunit production. ISSN:2666-3864 ISSN:2211-1247

Summary There is pressing urgency to understand the pathogenesis of the severe acute respiratory syndrome coronavirus clade 2 (SARS-CoV-2), which causes the disease COVID-19. SARS-CoV-2 spike (S) protein binds angiotensin-converting enzyme 2 (ACE2), and in concert with host proteases, principally transmembrane serine protease 2 (TMPRSS2), promotes cellular entry. The cell subsets targeted by SARS-CoV-2 in host tissues and the factors that regulate ACE2 expression remain unknown. Here, we leverage human, non-human primate, and mouse single-cell RNA-sequencing (scRNA-seq) datasets across health and disease to uncover putative targets of SARS-CoV-2 among tissue-resident cell subsets. We identify ACE2 and TMPRSS2 co-expressing cells within lung type II pneumocytes, ileal absorptive enterocytes, and nasal goblet secretory cells. Strikingly, we discovered that ACE2 is a human interferon-stimulated gene (ISG) in vitro using airway epithelial cells and extend our findings to in vivo viral infections. Our data suggest that SARS-CoV-2 could exploit species-specific interferon-driven upregulation of ACE2, a tissue-protective mediator during lung injury, to enhance infection., Graphical Abstract, Highlights • Meta-analysis of human, non-human primate, and mouse single-cell RNA-seq datasets for putative SARS-CoV-2 targets • Type II pneumocytes, nasal secretory cells, and absorptive enterocytes are ACE2 + TMPRSS2 + • Interferon and influenza increase ACE2 in human nasal epithelia and lung tissue • Mouse Ace2 is not upregulated by interferon, raising implications for disease modeling, Analysis of single-cell RNA-seq datasets from human, non-human primate, and mouse barrier tissues identifies putative cellular targets of SARS-CoV-2 on the basis of ACE2 and TMPRSS2 expression. ACE2 represents a previously unappreciated interferon-stimulated gene in human, but not mouse, epithelial tissues, identifying anti-viral induction of a host tissue-protective mechanism, but also a potential means for viral exploitation of the host response.