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Targeted spatial transcriptomic methods capture the topology of cell types and states in tissues at single-cell and subcellular resolution by measuring the expression of a predefined set of genes. The selection of an optimal set of probed genes is crucial for capturing the spatial signals present in a tissue. This requires selecting the most informative, yet minimal, set of genes to profile (gene set selection) for which it is possible to build probes (probe design). However, current selections often rely on marker genes, precluding them from detecting continuous spatial signals or new states. We present Spapros, an end-to-end probe set selection pipeline that optimizes both gene set specificity for cell type identification and within-cell type expression variation to resolve spatially distinct populations while considering prior knowledge as well as probe design and expression constraints. We evaluated Spapros and show that it outperforms other selection approaches in both cell type recovery and recovering expression variation beyond cell types. Furthermore, we used Spapros to design a single-cell resolution in situ hybridization on tissues (SCRINSHOT) experiment of adult lung tissue to demonstrate how probes selected with Spapros identify cell types of interest and detect spatial variation even within cell types., Competing Interests: Competing interests: F.J.T. consults for Immunai Inc., CytoReason Ltd, Cellarity and BioTuring Inc., and has an ownership interest in Dermagnostix GmbH and Cellarity. M.D.L. contracted for the Chan Zuckerberg Initiative and received speaker fees from Pfizer and Janssen Pharmaceuticals. P.H., F.K. and T.B. acknowledge support from TKP2021-EGA09, Horizon-BIALYMPH, -SYMMETRY, -SWEEPICS, -Fair-CHARM and OTKA-SNN 139455., (© 2024. The Author(s).)

Galectins are one of the critical players in the tumor microenvironment-tumor crosstalk and the regulation of local immunity. Galectin-9 has been in the limelight in tumor immunology. Galectin-9 possesses its multiplex biological functions both extracellularly and intracellularly, plays a pivotal role in the modulation of adaptive and innate immunity, and induces immune tolerance. NK-92MI cell lines against different malignancies were extensively studied, and recently published trials used genetically chimeric antigen receptor-transfected NK-92MI cells in tumor immunotherapy. Besides the intensive research in tumor immunotherapy, limited information is available on their immune-checkpoint expression and the impact of checkpoint ligands on their effector functions. To uncover the therapeutic potential of modulating Galectin-9-related immunological pathways in NK-cell-based therapy, we investigated the dose-dependent effect of soluble Galectin-9 on the TIM-3 checkpoint receptor and NKG2D, CD69, FasL, and perforin expression of NK-92MI cells. We also examined how their cytotoxicity and cytokine production was altered after Gal-9 treatment and in the presence of different serum supplements using flow cytometric analysis. Our study provides evidence that the Galectin-9/TIM-3 pathway plays an important role in the regulation of NK cell function, and about the modulatory role of Galectin-9 on the cytotoxicity and cytokine production of NK-92MI cells in the presence of different serum supplements. We hope that our results will aid the development of novel NK-cell-based strategies that target Galectin-9/TIM-3 checkpoint in tumors resistant to T-cell-based immunotherapy.

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.

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.

Background: Heat-shock protein B1 (HSPB1) is among the most well-known and versatile member of the evolutionarily conserved family of small heat-shock proteins. It has been implicated to serve a neuroprotective role against various neurological disorders via its modulatory activity on inflammation, yet its exact role in neuroinflammation is poorly understood. In order to shed light on the exact mechanism of inflammation modulation by HSPB1, we investigated the effect of HSPB1 on neuroinflammatory processes in an in vivo and in vitro model of acute brain injury., Methods: In this study, we used a transgenic mouse strain overexpressing the human HSPB1 protein. In the in vivo experiments, 7-day-old transgenic and wild-type mice were treated with ethanol. Apoptotic cells were detected using TUNEL assay. The mRNA and protein levels of cytokines and glial cell markers were examined using RT-PCR and immunohistochemistry in the brain. We also established primary neuronal, astrocyte, and microglial cultures which were subjected to cytokine and ethanol treatments. TNFα and hHSPB1 levels were measured from the supernates by ELISA, and intracellular hHSPB1 expression was analyzed using fluorescent immunohistochemistry., Results: Following ethanol treatment, the brains of hHSPB1-overexpressing mice showed a significantly higher mRNA level of pro-inflammatory cytokines (Tnf, Il1b), microglia (Cd68, Arg1), and astrocyte (Gfap) markers compared to wild-type brains. Microglial activation, and 1 week later, reactive astrogliosis was higher in certain brain areas of ethanol-treated transgenic mice compared to those of wild-types. Despite the remarkably high expression of pro-apoptotic Tnf, hHSPB1-overexpressing mice did not exhibit higher level of apoptosis. Our data suggest that intracellular hHSPB1, showing the highest level in primary astrocytes, was responsible for the inflammation-regulating effects. Microglia cells were the main source of TNFα in our model. Microglia isolated from hHSPB1-overexpressing mice showed a significantly higher release of TNFα compared to wild-type cells under inflammatory conditions., Conclusions: Our work provides novel in vivo evidence that hHSPB1 overexpression has a regulating effect on acute neuroinflammation by intensifying the expression of pro-inflammatory cytokines and enhancing glial cell activation, but not increasing neuronal apoptosis. These results suggest that hHSPB1 may play a complex role in the modulation of the ethanol-induced neuroinflammatory response.

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., (© 2020 The Authors.)

Single-cell segmentation is typically a crucial task of image-based cellular analysis. We present nucleAIzer, a deep-learning approach aiming toward a truly general method for localizing 2D cell 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 that during training nucleAIzer automatically adapts its nucleus-style model to unseen and unlabeled data using image style transfer to automatically generate augmented training samples. This allows the model to recognize nuclei in new and different experiments efficiently without requiring expert annotations, making deep learning for nucleus segmentation fairly simple and labor free for most biological light microscopy experiments. It can also be used online, integrated into CellProfiler and freely downloaded at www.nucleaizer.org. A record of this paper's transparent peer review process is included in the Supplemental Information., Competing Interests: DECLARATION OF INTERESTS The authors declare no competing interests.

Purpose: The most common hospital-acquired enteral infection is caused by Clostridium difficile. Unfortunately, Clostridium difficile infections (CDI) are of high risk to recur and little is known about how to predict recurrences. Previous findings have shown that high risk for recurrence correlates with low levels of C. difficile toxin-A and -B specific antibodies suggesting the protective role of humoral immunity against bacterial virulence factors. Therefore, the aim of this study was to develop an immunoassay, which specifically measures C.difficile toxin-specific antibodies in the serum that might be correlated with the risk of recurrence., Methods: We developed a simple ELISA to measure the quantity of toxin-A and -B-specific antibodies in human serum. The assay was then used to test anti-toxin immune response in healthy controls, in patients with primary CDI and patients with CDI recurrence., Results: The developed assay is simple, reproducible and fast. When using this test in a small clinical trial our results showed a trend toward a higher antibody level in those patients with only one episode of CDI, whereas patients with recurrent CDI had less anti-toxin A or B-specific antibodies in their serum indicating inadequate C. difficile anti-toxin immunity may facilitate recurrent infections., Conclusions: It has already been observed that low antibody levels are associated with recurrent CDI (Bauer et al., 2014). The findings of our clinical trial show a similar trend. Our developed ELISA test could help to conduct further research and it might be helpful in clinical use to detect patients of high risk for CDI recurrence., (Copyright © 2019 Elsevier B.V. All rights reserved.)

During assisted reproduction the embryos are subjected to light. We investigated the relationship between light exposure and the developmental- and implantation capacity of mouse embryos. In vitro cultured embryos were exposed to white or red filtered light, then transferred to the uteri of pseudo-pregnant females. The mice were sacrificed on day 8.5 and implantation sites were counted. The number of nucleic acid containing (PI+) extracellular vesicles (EVs) in culture media of light-exposed and control embryos, as well as, the effect of the EVs on IL-10 production of CD8+ spleen cells was determined by flow cytometry. DNA fragmentation in control and light exposed embryos was detected in a TUNEL assay. The effect of light on the expression of apoptosis-related molecules was assessed in an apoptosis array. Light exposure significantly reduced the implantation capacity of the embryos. The harmful effect was related to the wavelength, rather than to the brightness of the light. Culture media of light exposed groups contained significantly higher number of PI + EVs than those of the control embryos, and failed to induce IL-10 production of spleen cells. The number of nuclei with fragmented DNA, was significantly higher in embryos treated with white light, than in the other two groups. In conclusion exposure to white light impairs the implantation potential of in vitro cultured mouse embryos. These effects are partly corrected by using a red filter. Since there is no information on the light sensitivity of human embryos, embryo manipulation during IVF and ICSI should be performed with caution., (Copyright © 2019 Elsevier B.V. All rights reserved.)

Objective: The prevalence of hyperostosis frontalis interna (HFI) was examined in different periods of the Carpathian Basin from 4900 BCE to 17th century AD. The study seeks to evaluate temporal changes in HFI and the possible impact of lifestyle on it., Materials: The studied material consisted of 4668 crania from Hungary and Serbia., Methods: The crania were analyzed employing macroscopic and endoscopic examination., Results: In historic periods, sex and age played a pivotal role in HFI development. Among predominantly pastoralist populations of the 5th-8th and 10th centuries, prevalence of HFI was considerably higher than in the medieval populations of the 9th-17th centuries., Conclusions: In addition to age and sex, other factors could be implicated in HFI development. The physiological effects of the pastoralist lifestyle and diet on insulin regulation could explain the increased risk of developing HFI in the 5th-8th and 10th-century populations., Significance: The study provides the first comprehensive dataset of HFI from different archaeological periods from the Carpathian Basin. It has implications for lifestyle and risk of HFI development in past populations., Limitations: The archaeological periods are not equally represented., Suggestions for Further Research: In order to better understand the etiology of HFI, lifestyle factors can be used to elucidate the risk of developing HFI in ancient populations., (Copyright © 2018 Elsevier Inc. All rights reserved.)

Astrocytes are involved in various brain pathologies including trauma, stroke, neurodegenerative disorders such as Alzheimer's and Parkinson's diseases, or chronic pain. Determining cell density in a complex tissue environment in microscopy images and elucidating the temporal characteristics of morphological and biochemical changes is essential to understand the role of astrocytes in physiological and pathological conditions. Nowadays, manual stereological cell counting or semi-automatic segmentation techniques are widely used for the quantitative analysis of microscopy images. Detecting astrocytes automatically is a highly challenging computational task, for which we currently lack efficient image analysis tools. We have developed a fast and fully automated software that assesses the number of astrocytes using Deep Convolutional Neural Networks (DCNN). The method highly outperforms state-of-the-art image analysis and machine learning methods and provides precision comparable to those of human experts. Additionally, the runtime of cell detection is significantly less than that of other three computational methods analysed, and it is faster than human observers by orders of magnitude. We applied our DCNN-based method to examine the number of astrocytes in different brain regions of rats with opioid-induced hyperalgesia/tolerance (OIH/OIT), as morphine tolerance is believed to activate glia. We have demonstrated a strong positive correlation between manual and DCNN-based quantification of astrocytes in rat brain.

To answer major questions of cell biology, it is often essential to understand the complex phenotypic composition of cellular systems precisely. Modern automated microscopes produce vast amounts of images routinely, making manual analysis nearly impossible. Due to their efficiency, machine learning-based analysis software have become essential tools to perform single-cell-level phenotypic analysis of large imaging datasets. However, an important limitation of such methods is that they do not use the information gained from the cellular micro- and macroenvironment: the algorithmic decision is based solely on the local properties of the cell of interest. Here, we present how various features from the surrounding environment contribute to identifying a cell and how such additional information can improve single-cell-level phenotypic image analysis. The proposed methodology was tested for different sizes of Euclidean and nearest neighbour-based cellular environments both on tissue sections and cell cultures. Our experimental data verify that the surrounding area of a cell largely determines its entity. This effect was found to be especially strong for established tissues, while it was somewhat weaker in the case of cell cultures. Our analysis shows that combining local cellular features with the properties of the cell's neighbourhood significantly improves the accuracy of machine learning-based phenotyping.

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., (Copyright © 2018 Elsevier Inc. All rights reserved.)

In addition to being immunomodulatory, Progesterone-Induced Blocking Factor (PIBF) plays a role in cell cycle regulation and invasion. The full length protein is associated with the pericentriolar satellites and as such, it is crucial for maintaining the integrity of spindle poles during mitosis. Another suggestive evidence for the involvement of PIBF in tumour progression is the fact that the PIBF gene has been identified on chromosome 13 in the region associated with breast cancer susceptibility. Earlier we showed that PIBF differentially regulates the invasiveness of trophoblast and tumour cell lines. The aim of the present study was to further investigate the role of PIBF in tumour development, using primary ovarian- (OC) and primary lung carcinoma (LC) cell cultures, and JEG-3 choriocarcinoma cell line. In the cultured cells PIBF was knocked down by siRNA treatment, and the impact of PIBF deficiency on MMP-9 activity and E-cadherin expression as well as on invasive and migratory capacity of the cells was tested. In conditioned media of PIBF-deficient JEG-3 cells, LC cells and OC cells MMP-9 activity was reduced to 36% 35%, and 65% respectively compared to controls. Though PIBF knock down did not affect migration, in JEG-3 cells, LC primary cells and OC primary cells PIBF deficiency resulted 20%, 50% and 50% decrease of invasion respectively. PIBF silencing resulted in increased E-cadherin expression, suggesting that by down regulating E-cadherin expression, PIBF might interfere with the cell-cell adhesion mechanisms and by increasing MMP activity induced extracellular matrix degradation, facilitates the invasion of tumour cells., (Copyright © 2017 Elsevier B.V. All rights reserved.)

Proteins are necessary for cellular growth. Concurrently, however, protein production has high energetic demands associated with transcription and translation. Here, we propose that activity of molecular chaperones shape protein burden, that is the fitness costs associated with expression of unneeded proteins. To test this hypothesis, we performed a genome-wide genetic interaction screen in baker's yeast. Impairment of transcription, translation, and protein folding rendered cells hypersensitive to protein burden. Specifically, deletion of specific regulators of the Hsp70-associated chaperone network increased protein burden. In agreement with expectation, temperature stress, increased mistranslation and a chemical misfolding agent all substantially enhanced protein burden. Finally, unneeded protein perturbed interactions between key components of the Hsp70-Hsp90 network involved in folding of native proteins. We conclude that specific chaperones contribute to protein burden. Our work indicates that by minimizing the damaging impact of gratuitous protein overproduction, chaperones enable tolerance to massive changes in genomic expression., Competing Interests: ZF, DK, ZB, BS, AD, KA, KK, GB, FP, PH, TB, CM, AP, ÉK, ER, AS, BP, CP No competing interests declared, (© 2017, Farkas et al.)

Quantifying heterogeneities within cell populations is important for many fields including cancer research and neurobiology; however, techniques to isolate individual cells are limited. Here, we describe a high-throughput, non-disruptive, and cost-effective isolation method that is capable of capturing individually targeted cells using widely available techniques. Using high-resolution microscopy, laser microcapture microscopy, image analysis, and machine learning, our technology enables scalable molecular genetic analysis of single cells, targetable by morphology or location within the sample.

Vitamin D plays an important role in maintaining calcium and bone metabolism, a risk factor of osteoporosis, fall and fracture in old age. Reduction in D-vitamin levels associated with compensatory increased level of parathyroid hormone causes significant loss of bone matrix, so substitutions of vitamin D and calcium are very important. Many authors publish their recommended doses used for prevention of hip fracture during the last years. Some authors are satisfied only with vitamin D supplementation while others have better experiences with vitamin D and calcium substitution. On the other hand, some metaanalyses give contradictory results and propose further investigations. It is important to consider the patients' eating habits and lifestyle as well as the risk of cardiovascular and other chronic diseases. Further trials should be done in different age groups in order to examine the effects of different doses of vitamin D without and with calcium to make a final decision. Orv Hetil. 2017; 158(43): 1699-1707.

High-content, imaging-based screens now routinely generate data on a scale that precludes manual verification and interrogation. Software applying machine learning has become an essential tool to automate analysis, but these methods require annotated examples to learn from. Efficiently exploring large datasets to find relevant examples remains a challenging bottleneck. Here, we present Advanced Cell Classifier (ACC), a graphical software package for phenotypic analysis that addresses these difficulties. ACC applies machine-learning and image-analysis methods to high-content data generated by large-scale, cell-based experiments. It features methods to mine microscopic image data, discover new phenotypes, and improve recognition performance. We demonstrate that these features substantially expedite the training process, successfully uncover rare phenotypes, and improve the accuracy of the analysis. ACC is extensively documented, designed to be user-friendly for researchers without machine-learning expertise, and distributed as a free open-source tool at www.cellclassifier.org., (Copyright © 2017 Elsevier Inc. All rights reserved.)

Ancient DNA (aDNA) research involves invasive and destructive sampling procedures that are often incompatible with anthropological, anatomical, and bioarcheological analyses requiring intact skeletal remains. The osseous labyrinth inside the petrous bone has been shown to yield higher amounts of endogenous DNA than any other skeletal element; however, accessing this labyrinth in cases of a complete or reconstructed skull involves causing major structural damage to the cranial vault or base. Here, we describe a novel cranial base drilling method (CBDM) for accessing the osseous labyrinth from the cranial base that prevents damaging the surrounding cranial features, making it highly complementary to morphological analyses. We assessed this method by comparing the aDNA results from one petrous bone processed using our novel method to its pair, which was processed using established protocols for sampling disarticulated petrous bones. We show a decrease in endogenous DNA and molecular copy numbers when the drilling method is used; however, we also show that this method produces more endogenous DNA and higher copy numbers than any postcranial bone. Our results demonstrate that this minimally-invasive method reduces the loss of genetic data associated with the use of other skeletal elements and enables the combined craniometric and genetic study of individuals with archeological, cultural, and evolutionary value.

The decidua has been known as maternal uterine tissue, which plays essential roles in protecting the embryo from being attacked by maternal immune cells and provides nutritional support for the developing embryo prior to placenta formation. However, there are questions that still remain to be answered: (1) How does the decidua supply nutrition and provide a physical scaffold for the growing embryo, before placental vascular connection is established? (2) How is the balance between preventing an anti-embryo immune response and protecting both embryo and mother from infections established? To understand basic personas in decidual tissues, we review the structure of the decidua composed of terminally differentiated uterine stromal cells, blood vessels, and a number of repertoire of uterine local immune cells, including the well-known uterine natural killer (uNK) cells and recently discovered innate lymphoid cells (ILCs). Decidual macrophages and uterine dendritic cells (DCs) are supposed to modulate adaptive immunity via balancing cytokines and promoting generation of regulatory T (T reg ) cells. During decidualization, vascular and tissue remodeling in the uterus provide nutritional and physical support for the developing embryo. Secretion of various cytokines and chemokines from both the embryo and the decidual cells activates multiple signaling network between the mother and the embryo upon implantation. Defects in the decidual development during early pregnancy result in loss of pregnancy or complications in later gestational stage.

Background and Purpose: Introducing the multidisciplinary paleoradiology research at the Institute of Diagnostic Imaging and Radiation Oncology of the Kaposvár University, highlighting the cases with potential central nervous system involvement--from the scanning methods to the 3D printing--in order to draw attention to the historical background and clinical aspects of certain pathological conditions., Methods: The authors developed the examination protocols for three different CT scanners. Among the examined archaeological remains cranial lesions were identified in 26 cases, from which 4 cases with potential central nervous system involvement are demonstrated. The scanning parameters and the advantages of secondary image reconstructions (multiplanar reconstruction, maximum intensity projection, three-dimensional volume rendering technique) are presented with the cases., Results: The authors demonstrate a case with destructive skull lesions due to syphilis from the 15th century AD, a condition rarely seen or even unknown nowadays in the modern world. With the CT images of the skull base fracture from the Iron Age, signs of healing could be verified. Using the CT images a non-invasive approach is presented in the case of the craniofacial osteosarcoma in order to visualize the local status and the direct intracranial propagation. Advantages of the 3D VRT reconstructions are shown in the case of unilateral coronal suture synostosis., Conclusion: Paleoradiological CT examinations serve as a non-invasive, non-destructive tool for studying archaeological remains and artifacts. The special applications provided by the imaging modality contribute to the conventional paleopathological investigations.

An earlier study demonstrated changes in synaptic efficacy and seizure susceptibility in adult rat brain slices following extremely low-frequency magnetic field (ELF-MF) exposure. The developing embryonic and early postnatal brain may be even more sensitive to MF exposure. The aim of the present study was to determine the effects of a long-term ELF-MF (0.5 and 3 mT, 50 Hz) exposure on synaptic functions in the developing brain. Rats were treated with chronic exposure to MF during two critical periods of brain development, i.e. in utero during the second gestation week or as newborns for 7 days starting 3 days after birth, respectively. Excitability and plasticity of neocortical and hippocampal areas were tested on brain slices by analyzing extracellular evoked field potentials. We demonstrated that the basic excitability of hippocampal slices (measured as amplitude of population spikes) was increased by both types of treatment (fetal 0.5 mT, newborn 3 mT). Neocortical slices seemed to be responsive mostly to the newborn treatment, the amplitude of excitatory postsynaptic potentials was increased. Fetal ELF-MF exposure significantly inhibited the paired-pulse depression (PPD) and there was a significant decrease in the efficacy of LTP (long-term potentiation induction) in neocortex, but not in hippocampus. On the other hand, neonatal treatment had no significant effect on plasticity phenomena. Results demonstrated that ELF-MF has significant effects on basic neuronal functions and synaptic plasticity in brain slice preparations originating from rats exposed either in fetal or in newborn period., (Copyright © 2013 ISDN. Published by Elsevier Ltd. All rights reserved.)