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The effects of mercury complexes on human body and cells vary depending on the extent of exposure and their pharmacological form. Objectives: To characterize mercury complex and then investigate the effects on cellular interaction via cell death. Methods: The synthesis of the mercury complex was carried out, and its characterization was done by FTIR, elemental percentage and powder X-ray diffraction (PXRD). The complex was analyzed through atomic force microscopy (AFM) and by microscopy imaging its surface morphology and cellular interaction were also studied. Results: The presence of the mercury-complex results in cell death in concentration and time dependent manner. Conclusions: The synthesized mercury-complex has the ability to harm cells.

Fluorescence-based sensors play a fundamental role in biological research. These sensors can be based on fluorescent proteins, fluorescent probes or they can be hybrid systems. The availability of a very large dataset of fluorescent molecules, both genetically encoded and synthetically produced, together with the structural insights on many sensing domains, allowed to rationally design a high variety of sensors, capable of monitoring both molecular and global changes in living cells or in in vitro systems. The advancements in the fluorescence-imaging field helped researchers to obtain a deeper understanding of how and where specific changes occur in a cell or in vitro by combining the readout of the fluorescent sensors with the spatial information provided by fluorescent microscopy techniques. In this review we give an overview of the state of the art in the field of fluorescent biosensors and fluorescence imaging techniques, and eventually guide the reader through the choice of the best combination of fluorescent tools and techniques to answer specific biological questions. We particularly focus on sensors for probing the bioenergetics and physicochemical status of the cell.

Lanthanide-doped upconversion nanoparticles (UCNPs) are promising bioimaging nanoprobes due to their excellent photostability. As one of the most commonly used lanthanide activators, Tm3+ ions have perfect ladder-type electron configuration and can be directly excited by bio-friendly near-infrared-II (NIR-II) wavelengths. Here, the emission characteristics of Tm3+-doped nanoparticles under laser excitations of different near-infrared-II wavelengths were systematically investigated. The 1064 nm, 1150 nm, and 1208 nm lasers are proposed to be three excitation strategies with different response spectra of Tm3+ ions. In particular, we found that 1150 nm laser excitation enables intense three-photon 475 nm emission, which is nearly 100 times stronger than that excited by 1064 nm excitation. We further optimized the luminescence brightness after investigating the luminescence quenching mechanism of bare NaYF4: Tm (1.75%) core. After growing an inert shell, a ten-fold increase of emission intensity was achieved. Combining the advantages of NIR-II wavelength and the higher-order nonlinear excitation, a promising facile excitation strategy was developed for the application of thulium-doped upconversion nanoparticles in nanoparticles imaging and cancer cell microscopic imaging., QC 20210628

Fluorescence-based sensors play a fundamental role in biological research. These sensors can be based on fluorescent proteins, fluorescent probes or they can be hybrid systems. The availability of a very large dataset of fluorescent molecules, both genetically encoded and synthetically produced, together with the structural insights on many sensing domains, allowed to rationally design a high variety of sensors, capable of monitoring both molecular and global changes in living cells or in in vitro systems. The advancements in the fluorescence-imaging field helped researchers to obtain a deeper understanding of how and where specific changes occur in a cell or in vitro by combining the readout of the fluorescent sensors with the spatial information provided by fluorescent microscopy techniques. In this review we give an overview of the state of the art in the field of fluorescent biosensors and fluorescence imaging techniques, and eventually guide the reader through the choice of the best combination of fluorescent tools and techniques to answer specific biological questions. We particularly focus on sensors for probing the bioenergetics and physicochemical status of the cell.

Beneficial plant-microbe interactions offer a sustainable biological solution with the potential to boost low-input food and bioenergy production. A better mechanistic understanding of these complex plant-microbe interactions will be crucial to improving plant production as well as performing basic ecological studies investigating plant-soil-microbe interactions. Here, a detailed description for ecosystem fabrication is presented, using widely available 3D printing technologies, to create controlled laboratory habitats (EcoFABs) for mechanistic studies of plant-microbe interactions within specific environmental conditions. Two sizes of EcoFABs are described that are suited for the investigation of microbial interactions with various plant species, including Arabidopsis thaliana, Brachypodium distachyon, and Panicum virgatum. These flow-through devices allow for controlled manipulation and sampling of root microbiomes, root chemistry as well as imaging of root morphology and microbial localization. This protocol includes the details for maintaining sterile conditions inside EcoFABs and mounting independent LED light systems onto EcoFABs. Detailed methods for addition of different forms of media, including soils, sand, and liquid growth media coupled to the characterization of these systems using imaging and metabolomics are described. Together, these systems enable dynamic and detailed investigation of plant and plant-microbial consortia including the manipulation of microbiome composition (including mutants), the monitoring of plant growth, root morphology, exudate composition, and microbial localization under controlled environmental conditions. We anticipate that these detailed protocols will serve as an important starting point for other researchers, ideally helping create standardized experimental systems for investigating plant-microbe interactions.

Beneficial plant-microbe interactions offer a sustainable biological solution with the potential to boost low-input food and bioenergy production. A better mechanistic understanding of these complex plant-microbe interactions will be crucial to improving plant production as well as performing basic ecological studies investigating plant-soil-microbe interactions. Here, a detailed description for ecosystem fabrication is presented, using widely available 3D printing technologies, to create controlled laboratory habitats (EcoFABs) for mechanistic studies of plant-microbe interactions within specific environmental conditions. Two sizes of EcoFABs are described that are suited for the investigation of microbial interactions with various plant species, including Arabidopsis thaliana, Brachypodium distachyon, and Panicum virgatum. These flow-through devices allow for controlled manipulation and sampling of root microbiomes, root chemistry as well as imaging of root morphology and microbial localization. This protocol includes the details for maintaining sterile conditions inside EcoFABs and mounting independent LED light systems onto EcoFABs. Detailed methods for addition of different forms of media, including soils, sand, and liquid growth media coupled to the characterization of these systems using imaging and metabolomics are described. Together, these systems enable dynamic and detailed investigation of plant and plant-microbial consortia including the manipulation of microbiome composition (including mutants), the monitoring of plant growth, root morphology, exudate composition, and microbial localization under controlled environmental conditions. We anticipate that these detailed protocols will serve as an important starting point for other researchers, ideally helping create standardized experimental systems for investigating plant-microbe interactions.

In this study, the use of light sheet fluorescence microscopic imaging is demonstrated for viewing the dynamic of atomizing sprays with high contrast and resolution. The technique presents several advantages. First, liquid fluorescence gives a more faithful representation of the structure of liquid bodies, droplets, and ligaments than Mie scattering does. The reason for this is that the signal is emitted by the fluorescing dye molecules inside the liquid itself and not generated at the air–liquid interfaces. Second, despite the short depth of field (∼200 µm) obtained when using the long range microscope, the contribution of out-of-focus light is much smaller on a light sheet configuration than for line-of-sight detection, thus providing more clearly sectioned images. Finally, by positioning the light sheet on the spray periphery, toward the camera objective, the effects due to multiple light scattering phenomena can be reduced to some extent. All these features provide, for many spray situations, good fidelity images of the liquid fluid, allowing the extraction of the velocity vectors at the liquid boundaries. Here, double frame images were recorded with a sCMOS camera with a time delay of 5 µs between exposures. A typical pressure-swirl atomizer is used producing a water hollow-cone spray, which was imaged in the near-nozzle region and further downstream for injection pressures between 20 bar and 100 bar. Furthermore, near-nozzle spray shape visualization of a direct-injection spark ignition injector was conducted, describing the disintegration of the liquid fuel and droplet formation. Such data are important for the validation of computational fluid dynamics models simulating liquid breakups in the near-field spray region.

White blood cell (WBC) count and segmentation is considered to be important step to diagnose diseases like leukemia, malaria etc. Automatic analysis of blood smear images will help hematologists to detect WBCs efficiently and effectively as compared to manual analysis which is quite time consuming. Therefore, an automatic white blood cells detection technique for complex blood smear images is proposed. The proposed scheme uses segmentation and edge map extraction for the separation of overlapped WBCs and further parametric circle approximation is used which is capable of detecting both separated and overlapped white blood cells. Simulation results compared with the existing techniques verify the accuracy and robustness of the proposed scheme.

White blood cell (WBC) count and segmentation is considered to be important step to diagnose diseases like leukemia, malaria etc. Automatic analysis of blood smear images will help hematologists to detect WBCs efficiently and effectively as compared to manual analysis which is quite time consuming. Therefore, an automatic white blood cells detection technique for complex blood smear images is proposed. The proposed scheme uses segmentation and edge map extraction for the separation of overlapped WBCs and further parametric circle approximation is used which is capable of detecting both separated and overlapped white blood cells. Simulation results compared with the existing techniques verify the accuracy and robustness of the proposed scheme.

White blood cell (WBC) count and segmentation is considered to be important step to diagnose diseases like leukemia, malaria etc. Automatic analysis of blood smear images will help hematologists to detect WBCs efficiently and effectively as compared to manual analysis which is quite time consuming. Therefore, an automatic white blood cells detection technique for complex blood smear images is proposed. The proposed scheme uses segmentation and edge map extraction for the separation of overlapped WBCs and further parametric circle approximation is used which is capable of detecting both separated and overlapped white blood cells. Simulation results compared with the existing techniques verify the accuracy and robustness of the proposed scheme.

White blood cell (WBC) count and segmentation is considered to be important step to diagnose diseases like leukemia, malaria etc. Automatic analysis of blood smear images will help hematologists to detect WBCs efficiently and effectively as compared to manual analysis which is quite time consuming. Therefore, an automatic white blood cells detection technique for complex blood smear images is proposed. The proposed scheme uses segmentation and edge map extraction for the separation of overlapped WBCs and further parametric circle approximation is used which is capable of detecting both separated and overlapped white blood cells. Simulation results compared with the existing techniques verify the accuracy and robustness of the proposed scheme.

Using LAURDAN spectral imaging and spectral phasor analysis we concurrently studied the growth and hydration state of subcellular organelles (lamellar body-like, LB-like) from live A549 lung cancer cells at different post-confluence days. Our results reveal a time dependent two-step process governing the size and hydration of these intracellular LB-like structures. Specifically, a first step (days 1 to 7) is characterized by an increase in their size, followed by a second one (days 7 to 14) where the organelles display a decrease in their global hydration properties. Interestingly, our results also show that their hydration properties significantly differ from those observed in well-characterized artificial lamellar model membranes, challenging the notion that a pure lamellar membrane organization is present in these organelles at intracellular conditions. Finally, these LB-like structures show a significant increase in their hydration state upon secretion, suggesting a relevant role of entropy during this process.

Cellular imaging is an exciting area of research in computational life sciences, which provides an essential tool for the study of diseases at the cellular level. In particular, to faciliate the usefulness of cellular imaging for high content screening, image analysis and classification need to be automated. In fact the task of image classification is an important component for any computerized imaging system which aims to automate the screening of high-content, high-throughput fluorescent images of mitotic cells. It can help biomedical and biological researchers to speed up the analysis of mitotic data at dynamic ranges for various applications including the study of the complexity of cell processes, and the screening of novel anti-mitotic drugs as potential cancer therapeutic agents. We propose in this paper a novel image feature based on a spatial linear predictive model. This type of image feature can be effectively used for vector-quantization based classification of nuclear phases. We used a dataset of HeLa cells line to evaluate and compare the proposed method on the classification of nuclear phases. Experimental results obtained from the new feature are found to be superior to some recently published results using the same dataset.

Morimatsu M., Yamashita E., Seno S., et al. Migration arrest of chemoresistant leukemia cells mediated by MRTF-SRF pathway. Inflammation and Regeneration 40, 15 (2020); https://doi.org/10.1186/s41232-020-00127-6., Background: Dormant chemotherapy-resistant leukemia cells can survive for an extended period before relapse. Nevertheless, the mechanisms underlying the development of chemoresistance in vivo remain unclear. Methods: Using intravital bone imaging, we characterized the behavior of murine acute myeloid leukemia (AML) cells (C1498) in the bone marrow before and after chemotherapy with cytarabine. Results: Proliferative C1498 cells exhibited high motility in the bone marrow. Cytarabine treatment impaired the motility of residual C1498 cells. However, C1498 cells regained their migration potential after relapse. RNA sequencing revealed that cytarabine treatment promoted MRTF-SRF pathway activation. MRTF inhibition using CCG-203971 augmented the anti-tumor effects of chemotherapy in our AML mouse model, as well as suppressed the migration of chemoresistant C1498 cells. Conclusions: These results provide novel insight into the role of cell migration arrest on the development of chemoresistance in AML, as well as provide a strong rationale for the modulation of cellular motility as a therapeutic target for refractory AML.

Morimatsu M., Yamashita E., Seno S., et al. Migration arrest of chemoresistant leukemia cells mediated by MRTF-SRF pathway. Inflammation and Regeneration 40, 15 (2020); https://doi.org/10.1186/s41232-020-00127-6., Background: Dormant chemotherapy-resistant leukemia cells can survive for an extended period before relapse. Nevertheless, the mechanisms underlying the development of chemoresistance in vivo remain unclear. Methods: Using intravital bone imaging, we characterized the behavior of murine acute myeloid leukemia (AML) cells (C1498) in the bone marrow before and after chemotherapy with cytarabine. Results: Proliferative C1498 cells exhibited high motility in the bone marrow. Cytarabine treatment impaired the motility of residual C1498 cells. However, C1498 cells regained their migration potential after relapse. RNA sequencing revealed that cytarabine treatment promoted MRTF-SRF pathway activation. MRTF inhibition using CCG-203971 augmented the anti-tumor effects of chemotherapy in our AML mouse model, as well as suppressed the migration of chemoresistant C1498 cells. Conclusions: These results provide novel insight into the role of cell migration arrest on the development of chemoresistance in AML, as well as provide a strong rationale for the modulation of cellular motility as a therapeutic target for refractory AML.