Fluorescence Microscopy Images Research Articles

Effect of Collagen Matrix on Doxorubicin Distribution and Cancer Cells' Response to Treatment in 3D Tumor Model.

The extracellular matrix (ECM) plays an important role in regulation of many aspects of tumor growth and response to therapies. However, the specifics of the interaction of chemotherapeutic agents with cancer cells in the presence of collagen, the major component of ECM, is still poorly investigated. In this study, we explored distribution of doxorubicin (DOX) and its effects on cancer cells' metabolism in the presence of collagen with different structures in 3D models. For this, a combination of second harmonic generation imaging of collagen and multiphoton fluorescence microscopy of DOX, and metabolic cofactor NAD(P)H was used. It was found that collagen slowed down the diffusion of DOX and thus decreased the cellular drug uptake. Besides nuclei, DOX also targeted mitochondria leading to inhibition of oxidative phosphorylation, which was more pronounced in the cells growing in the absence of collagen. As a result, the cells in collagen displayed better viability upon treatment with DOX. Taken together, our data illustrate that tumor collagen contributes to heterogeneous and sub-optimal response to DOX and highlight the challenges in improving drug delivery and efficacy.

Advancing the Compositional Analysis of Olefin Polymerization Catalysts with High-Throughput Fluorescence Microscopy.

To optimize the performance of supported olefin polymerization catalysts, novel methodologies are required to evaluate the composition, structure, and morphology of both pristine and prepolymerized samples in a resource-efficient, high-throughput manner. Here, we report on a unique combination of laboratory-based confocal fluorescence microscopy and advanced image processing that allowed us to quantitatively assess support fragmentation in a large number of autofluorescent metallocene-based catalyst particles. Using this approach, significant inter- and intraparticle heterogeneities were detected and quantified in a representative number of prepolymerized catalyst particles (2D: ≥135, 3D: 40). The heterogeneity that was observed over several stages of slurry-phase ethylene polymerization (10 bar) is primarily attributed to the catalyst particles' diverse support structures and to the inhomogeneities in the metallocene distribution. From a mechanistic point of view, the 2D and 3D analyses revealed extensive contributions from a layer-by-layer fragmentation mechanism in synergy with a less pronounced sectioning mechanism. A significant number of catalyst particles were also found to display limited support fragmentation at the onset of the reaction (i.e., at lower polymer yields). This delay in activity or "dormancy" is believed to contribute to a broadening of the particle size distribution during the early stages of polymerization. 2D and 3D catalyst screening via confocal fluorescence microscopy represents an accessible and fast approach to characterize the structure of heterogeneous catalysts and assess the distribution of their fluorescent components and reaction products. The automation of both image segmentation and postprocessing with machine learning can yield a powerful diagnostic tool for future research as well as quality control on industrial catalysts.

Suitability of lectin binding studies for the characterization of redox-active microbial environmental biofilms

Aquatic environmental microbial biofilms grow in a broad range of redox environments from oxic to methanogenic, and they often also establish internal redox gradients. In technical applications, biofilms are also subjected to controlled redox conditions. Studies on biofilms often make use of fluorescence microscopic imaging techniques together with lectin binding analysis to gain insights into structure, composition, and functions of the biofilms. Here we studied the direct influence of redox potentials on fluorescence lectin binding analyses (FLBA) for two commonly used lectin-fluorophore conjugates. An effect of the electrical potential on signal intensity was observed and found to be statistically significant. The signal intensity changes however, remained within the range of a few percent total. A significant drop in intensity was only observed for extremely oxidizing potentials, typically not found under environmental conditions. Our results showed that the fluorophore itself and not the lectin binding to the respective glycoconjugate causes fluorescence changes. The two tested lectin-fluorophores are shown to be suitable for studying the distribution and composition of EPS in environmental biofilms or technical applications and under varying redox conditions.

Cellular adaptations leading to coral fragment attachment on artificial substrates in Acropora millepora (Am-CAM)

Reproductive propagation by asexual fragmentation in the reef-building coral Acropora millepora depends on (1) successful attachment to the reef substrate through modification of soft tissues and (2) a permanent bond with skeletal encrustation. Despite decades of research examining asexual propagation in corals, the initial response, cellular reorganisation, and development leading to fragment substrate attachment via a newly formed skeleton has not been documented in its entirety. Here, we establish the first "coral attachment model" for this species ("Am-CAM") by developing novel methods that allow correlation of fluorescence and electron microscopy image data with in vivo microscopic time-lapse imagery. This multi-scale imaging approach identified three distinct phases involved in asexual propagation: (1) the contact response of the coral fragment when contact with the substrate, followed by (2) fragment stabilisation through anchoring by the soft tissue, and (3) formation of a "lappet-like appendage" structure leading to substrate bonding of the tissue for encrustation through the onset of skeletal calcification. In developing Am-CAM, we provide new biological insights that can enable reef researchers, managers and coral restoration practitioners to begin evaluating attachment effectiveness, which is needed to optimise species-substrate compatibility and achieve effective outplanting.

Augmented Equivariant Attention Networks for Microscopy Image Transformation.

It is time-consuming and expensive to take high-quality or high-resolution electron microscopy (EM) and fluorescence microscopy (FM) images. Taking these images could be even invasive to samples and may damage certain subtleties in the samples after long or intense exposures, often necessary for achieving high-quality or high-resolution in the first place. Advances in deep learning enable us to perform various types of microscopy image-to-image transformation tasks such as image denoising, super-resolution, and segmentation that computationally produce high-quality images from the physically acquired low-quality ones. When training image-to-image transformation models on pairs of experimentally acquired microscopy images, prior models suffer from performance loss due to their inability to capture inter-image dependencies and common features shared among images. Existing methods that take advantage of shared features in image classification tasks cannot be properly applied to image transformation tasks because they fail to preserve the equivariance property under spatial permutations, something essential in image-to-image transformation. To address these limitations, we propose the augmented equivariant attention networks (AEANets) with better capability to capture inter-image dependencies, while preserving the equivariance property. The proposed AEANets captures inter-image dependencies and shared features via two augmentations on the attention mechanism, which are the shared references and the batch-aware attention during training. We theoretically derive the equivariance property of the proposed augmented attention model and experimentally demonstrate its consistent superiority in both quantitative and visual results over the baseline methods.

Multifunctional Oxygenated Particles for Targeted Cancer Drug Delivery and Evaluation with Darkfield Hyperspectral Imaging.

We propose a novel multifunctional nanocarrier system for targeted drug delivery for lung cancer theranostics. Oxygenated particles (OPs) synthesized with an oxygen-encapsulating carboxymethyl cellulose shell were used as a platform to deliver oxygen to the hypoxic tumor microenvironment. The OPs synthesized could also be conjugated with ligands (e.g., antibodies) to target cancer cells expressing the corresponding antigens to deliver a drug, doxorubicin. In vitro testing of functionalized OPs showed increased efficacy of doxorubicin against the proliferation of lung cancer cells. Both confocal fluorescence imaging and darkfield microscopy hyperspectral imaging validated the OP complex and its efficient targeting of specific cells to deliver the therapeutic. The nanocarrier platform developed can also serve as a diagnostic imaging reagent as demonstrated by darkfield microscopy. Results show that the theranostic OPs developed with multifunctional modalities enabled targeted drug delivery with improved efficacy and tracking of drug delivery vehicles by imaging.

Advanced glycation end products modulate electrophysiological remodeling of right ventricular outflow tract cardiomyocytes: A novel target for diabetes-related ventricular arrhythmogenesis.

Diabetes mellitus is associated with cardiovascular disease and cardiac arrhythmia. Accumulation of advanced glycation end products closely correlates with cardiovascular complications through mitochondrial dysfunction or oxidative stress and evoke proliferative, inflammatory, and fibrotic reactions, which might impair cardiac electrophysiological characteristics and increase the incidence of cardiac arrhythmia. This study examined the mechanisms how advanced glycation end products may contribute to arrhythmogenesis of right ventricular outflow tract-a unique arrhythmogenic substrate. A whole-cell patch clamp, conventional electrophysiological study, fluorescence imaging, Western blot, and confocal microscope were used to study the electrical activity, and Ca2+ homeostasis or signaling in isolated right ventricular outflow tract myocytes with and without advanced glycation end products (100 μg/ml). The advanced glycation end products treated right ventricular outflow tract myocytes had a similar action potential duration as the controls, but exhibited a lower L-type Ca2+ current, higher late sodium current and transient outward current. Moreover, the advanced glycation end products treated right ventricular outflow tract myocytes had more intracellular Na+ , reverse mode Na+ -Ca2+ exchanger currents, intracellular and mitochondrial reactive oxygen species, and less intracellular Ca2+ transient and sarcoplasmic reticulum Ca2+ content with upregulated calcium homeostasis proteins and advanced glycation end products related signaling pathway proteins. In conclusions, advanced glycation end products modulate right ventricular outflow tract electrophysiological characteristics with larger late sodium current, intracellular Na+ , reverse mode Na+ -Ca2+ exchanger currents, and disturbed Ca2+ homeostasis through increased oxidative stress mediated by the activation of the advanced glycation end products signaling pathway.

Alginic Acid Beads Containing Fluorescent Solvatochromic Dyes Display an Emission Color Response to a Cationic Surfactant.

Lipophilic fluorescent dyes can be employed as sensors for surfactants present in concentrations above the critical micellar concentration (CMC) where the dyes are monodispersed in micelles. However, the surfactant concentration range over which these dyes are effective is narrowed because by the sigmoidal nature of their responses. To overcome this limitation, we developed a novel sensor material comprised of a labeled fluorescent solvatochromic dye covalently bonded to alginate gel, which is known to strongly adsorb cationic surfactants. We hypothesized that the dye-alginate conjugate would undergo fluorescent color changes in response to binding of surfactants which alter the polarity of the surrounding environment. Indeed, addition of the representative cationic surfactant, cetylpyridinium chloride (CPC), to an aqueous solution of the alginate conjugated fluorescent solvatochromic dye leads to a visible fluorescent color change when the concentration of CPC is below the CMC. The average values of the color appearance parameter, referred to as a hue, of light emitted from gels, calculated by analysis of fluorescence microscopy images using ImageJ software, were found to be approximately linearly dependent on the concentration of CPC encapsulated in the alginate-fluorescent dye complex. This finding shows that absorbed CPC can be quantitatively determined over a wide concentration range in the form of simple fluorescence wavelength or visible responses.

DEEMD: Drug Efficacy Estimation Against SARS-CoV-2 Based on Cell Morphology With Deep Multiple Instance Learning

Drug repurposing can accelerate the identification of effective compounds for clinical use against SARS-CoV-2, with the advantage of pre-existing clinical safety data and an established supply chain. RNA viruses such as SARS-CoV-2 manipulate cellular pathways and induce reorganization of subcellular structures to support their life cycle. These morphological changes can be quantified using bioimaging techniques. In this work, we developed DEEMD: a computational pipeline using deep neural network models within a multiple instance learning framework, to identify putative treatments effective against SARS-CoV-2 based on morphological analysis of the publicly available RxRx19a dataset. This dataset consists of fluorescence microscopy images of SARS-CoV-2 non-infected cells and infected cells, with and without drug treatment. DEEMD first extracts discriminative morphological features to generate cell morphological profiles from the non-infected and infected cells. These morphological profiles are then used in a statistical model to estimate the applied treatment efficacy on infected cells based on similarities to non-infected cells. DEEMD is capable of localizing infected cells via weak supervision without any expensive pixel-level annotations. DEEMD identifies known SARS-CoV-2 inhibitors, such as Remdesivir and Aloxistatin, supporting the validity of our approach. DEEMD can be explored for use on other emerging viruses and datasets to rapidly identify candidate antiviral treatments in the future. Our implementation is available online at https://www.github.com/Sadegh-Saberian/DEEMD.

Didemnin B and ternatin-4 differentially inhibit conformational changes in eEF1A required for aminoacyl-tRNA accommodation into mammalian ribosomes.

Rapid and accurate mRNA translation requires efficient codon-dependent delivery of the correct aminoacyl-tRNA (aa-tRNA) to the ribosomal A site. In mammals, this fidelity-determining reaction is facilitated by the GTPase elongation factor-1 alpha (eEF1A), which escorts aa-tRNA as an eEF1A(GTP)-aa-tRNA ternary complex into the ribosome. The structurally unrelated cyclic peptides didemnin B and ternatin-4 bind to the eEF1A(GTP)-aa-tRNA ternary complex and inhibit translation but have different effects on protein synthesis in vitro and in vivo. Here, we employ single-molecule fluorescence imaging and cryogenic electron microscopy to determine how these natural products inhibit translational elongation on mammalian ribosomes. By binding to a common site on eEF1A, didemnin B and ternatin-4 trap eEF1A in an intermediate state of aa-tRNA selection, preventing eEF1A release and aa-tRNA accommodation on the ribosome. We also show that didemnin B and ternatin-4 exhibit distinct effects on the dynamics of aa-tRNA selection that inform on observed disparities in their inhibition efficacies and physiological impacts. These integrated findings underscore the value of dynamics measurements in assessing the mechanism of small-molecule inhibition and highlight potential of single-molecule methods to reveal how distinct natural products differentially impact the human translation mechanism.

An ultrasensitive detection platform for cocaine: Aptasensing strategy in capillary tube.

Cocaine as a detrimental addictive drug threats human health through inducing heart problem, blood pressure, anxiety, immunodeficiency, paranoia, and organ damage. Thus, the quantification of cocaine in the biological samples by a simple, high specificity, and fast method is highly urgent to decrease the harmful effect of the misuse of this drug. In this study, we constructed a novel fluorescent aptasensor by combining the fluorescein (FAM)-modified specific aptamer and AuNPs in a capillary tube as the sensing substrate for the first time. The presence of cocaine recovered the fluorescence response of the aptasensor through interaction with the aptamer and differentiation of the aptamer@AuNPs complex. By fluorescence microscopy imaging of the aptasensor substrate and its quantitative analysis, a remarkable linear range from 100pM to 600µM and the ultra-low limit of detection (LOD) as 0.31pM were achieved for the target detection. Cocaine was successfully quantified in the real samples (human serum and urine) by using the aptasensor. The aptasensor is simple, easy-to-use, favorable applicability, and cost-effective; and to the best of our knowledge, it is the first use of the capillary tube as a sensing platform just by using about 3μl of the samples. It is also an easy-to-carry tool, promising for the on-site target detection. Besides, it can be a portable device for monitoring cocaine by using a handheld single-beam fluorescence microscope. It can be an appropriate detection tool in forensic science and medicine.

Assessment of liver function-related mRNA expression and fluorescence imaging in outflow-obstructed regions in rats.

The liver function in outflow-obstructed regions is reportedly impaired; however, the functional decrease has not been quantitatively assessed. We therefore evaluated the uptake of indocyanine green (ICG) into hepatocytes and the mRNA expression associated with the liver function in outflow-obstructed regions using rat models. A total of 20 rats with the ligation of the right median hepatic vein to induce outflow obstruction were studied. Five rats each were grouped by the time of re-laparotomy, and the fluorescence intensity (FI) values of ICG. The mRNA expression, including that of Albumin, Cytochrome P450 (Cyp) 1a2, Cyp3a1, Cyp7a1, and Gamma-glutamylcysteine synthetase, in outflow-obstructed (mRNAOut-Ob) and non-outflow-obstructed (mRNANon) regions was assessed. Microscopic fluorescence imaging showed that the FI values were significantly lower in outflow-obstructed regions than in non-outflow-obstructed regions at 12h, 24h, and 3days after ligation of the hepatic vein. The mRNAOut-Ob/mRNANon ratios decreased to approximately 30% at 12h after the outflow obstruction and increased to approximately 70-80% at 7days. The liver function in outflow-obstructed regions was impaired in terms of the uptake of ICG and the mRNA expression. Our findings may help estimate the postoperative functional remnant liver volume by considering the decrease in the liver function in outflow-obstructed regions.

One-step synthesized antimicrobial peptide-functionalized gold nanoclusters for selective imaging and killing of pathogenic bacteria.

The development of multifunctional nanomaterials with bacterial imaging and killing activities is of great importance for the rapid diagnosis and timely treatment of bacterial infections. Herein, peptide-functionalized gold nanoclusters (CWR11-AuNCs) with high-intensity red fluorescence were successfully synthesized via a one-step method using CWR11 as a template and by optimizing the ratio of CWR11 to HAuCl4, reaction time, pH, and temperature. The CWR11-AuNCs bound to bacteria and exhibited selective fluorescence microscopy imaging properties, which is expected to provide a feasible method for locating and imaging bacteria in complex in vivo environments. In addition, CWR11-AuNCs not only retained the antibacterial and bactericidal activities of CWR11 but also exhibited certain inhibitory or killing effects on gram-negative and gram-positive bacteria and biofilms. The MICs of CWR11-AuNCs against Escherichia coli and Staphylococcus aureus were 178 and 89 μg/ml, respectively. Surprisingly, cell viability in the CWR11-AuNC-treated group was greater than that in the CWR11-treated group, and the low cytotoxicity exhibited by the CWR11-AuNCs make them more promising for clinical applications.

Photoluminescence sensing of Pb2+ using cellulose acetate nanofiber decorated with Au nanoparticles

Lead (II) is the second most hazardous heavy metal to the environment and humanity, due to its accumulation in the food chain and remaining as a persistent toxin in the environment. Thus, the design and fabrication of effective sensing materials and devices for the speedy detection of lead is a great challenge. Herein, we introduce gold nanoparticles deposited on the surface of electrospun cellulose acetate nanofiber Au@CANFs as photoluminescence sensor for detecting trace amount of lead metal ions based on a photoluminescence quenching approach. Despite that the concentration of cellulose acetate used for fabrication of nanofiber is lower than that previously reported, we observed nanofiber with small diameter and uniform shape. The scanning electron microscopy (SEM) and energy dispersive X-ray (EDX) analysis of the as-prepared sensor reveal the formation of nanofiber structure with diameter 90–200 nm and Au NPs are distributed on the surface of nanofiber with size 15–50 nm. The surface structure and chemical compositions of Au@CANFs were performed by Fourier transform infrared (FTIR) and XPS techniques. The UV-Vis spectra, clearly demonstrating that the sensor displayed localized surface plasmon resonance (LSPR) of Au nanoparticles. Both photoluminescence spectroscopy and Inverted Fluorescence microscopy image demonstrating that the CANFs and Au@CANFs display green emission. Under optimum conditions, the Au@CANFs PL sensor showed high sensitivity for detection of Pb2+ ion within a working range of 0 μg/L to 6 μg/L, R2 = 0.992 and a limit of detection of 0.16 ppb. Based on the obtained results, we anticipate that this PL sensor can be easily extended to tune the sensing performance of different heavy metals.

DeepNoise: Signal and Noise Disentanglement Based on Classifying Fluorescent Microscopy Images via Deep Learning

The high-content image-based assay is commonly leveraged for identifying the phenotypic impact of genetic perturbations in biology field. However, a persistent issue remains unsolved during experiments: the interferential technical noises caused by systematic errors (e.g., temperature, reagent concentration, and well location) are always mixed up with the real biological signals, leading to misinterpretation of any conclusion drawn. Here, we reported a mean teacher-based deep learning model (DeepNoise) that can disentangle biological signals from the experimental noises. Specifically, we aimed to classify the phenotypic impact of 1108 different genetic perturbations screened from 125,510 fluorescent microscopy images, which were totally unrecognizable by the human eye. We validated our model by participating in the Recursion Cellular Image Classification Challenge, and DeepNoise achieved an extremely high classification score (accuracy: 99.596%), ranking the 2nd place among 866 participating groups. This promising result indicates the successful separation of biological and technical factors, which might help decrease the cost of treatment development and expedite the drug discovery process. The source code of DeepNoise is available at https://github.com/Scu-sen/Recursion-Cellular-Image-Classification-Challenge.

Inferring the shape of data: a probabilistic framework for analysing experiments in the natural sciences.

A critical step in data analysis for many different types of experiments is the identification of features with theoretically defined shapes in -dimensional datasets; examples of this process include finding peaks in multi-dimensional molecular spectra or emitters in fluorescence microscopy images. Identifying such features involves determining if the overall shape of the data is consistent with an expected shape; however, it is generally unclear how to quantitatively make this determination. In practice, many analysis methods employ subjective, heuristic approaches, which complicates the validation of any ensuing results-especially as the amount and dimensionality of the data increase. Here, we present a probabilistic solution to this problem by using Bayes' rule to calculate the probability that the data have any one of several potential shapes. This probabilistic approach may be used to objectively compare how well different theories describe a dataset, identify changes between datasets and detect features within data using a corollary method called Bayesian Inference-based Template Search; several proof-of-principle examples are provided. Altogether, this mathematical framework serves as an automated 'engine' capable of computationally executing analysis decisions currently made by visual inspection across the sciences.

Spatial Transcriptomics-Based Identification of Molecular Markers for Nanomedicine Distribution in Tumor Tissue.

The intratumoral accumulation of nanomedicine has been considered a passive process, referred to as the enhanced permeability and retention effect. Recent studies have suggested that the tumor uptake of nanomedicines follows an energy-dependent pathway rather than being a passive process. Herein, to explore the factor candidates that are associated with nanomedicine tumor uptake, a molecular marker identification platform is developed by integrating microscopic fluorescence images of a nanomedicine distribution with spatial transcriptomics information. When this approach is applied to PEGylated liposomes, molecular markers related to hypoxia, glycolysis, and apoptosis can be identified as being related to the intratumoral distribution of the nanomedicine. It is expected that the method can be applied to explain the distribution of a wide range of nanomedicines and that the data obtained from this analysis can enhance the precise utilization of nanomedicines.

A dynamic thiol-disulfide exchange assisted high cell-penetrating fluorescent probe for intracellular H2S detection

Hydrogen sulfide (H2S) is a gaseous signaling transmitter which plays a crucial role in cell fates. Given the volatility of H2S in live cells corresponding to the various cell activities, it is important to design and synthesize novel fluorescent probes which could enter cells rapidly for the fast H2S detection. Herein, we reported a turn-on fluorescent probe P1 for H2S labeling in live cells, based on the dynamic thiol-disulfide exchange mechanism on cell surface, which facilitated the probe to enter cells quickly. High performance liquid chromatography (HPLC) results indicated the decoration of cell-penetrating disulfides endowed P1 with a high cellular uptake efficiency. Fluorescence microscopic imaging for HeLa cells suggested P1 was competent for intracellular H2S detection at submicromolar level. We expected our simple but effect strategy which enhanced the cell permeability of probes to benefit more accurate detection for intracellular specific molecule.

S5.3d How mitochondrial complex I proteins in Candida albicans moderate phagocytosis and the production of pro-inflammatory cytokines in murine macrophages and dendritic cells

S5.3 Cellular pleomorphism and fungal virulence, September 22, 2022, 3:00 PM - 4:30 PM ObjectivesInhibition of respiration in Candida albicans impairs its colonization in the host tissues and causes avirulence in a murine vascular candidiasis model. Accordingly, blockage of the mitochondrial electron transport chain (ETC) of C. albicans by respiratory inhibitors promotes phagocytosis by increasing exposure of glucan which could be due to the mannan reduction. In our model, we have reported that 85% mannan reduction in goa1Δ, a deletion mutant of an ETC Complex I (CI) regulator, oppositely decreased phagocytosis. To understand such a difference, we broaden our investigation with three CI respiratory subunit mutants, which are either fungal-specific (nuo1Δ and nuo2Δ) or broadly conserved subunits (ndh51Δ) for cell wall analysis and innate immune responses.MethodsWe characterized mutant cell wall defects in these mutants, then analyzed their respective survival in macrophages. Fungal internalization into macrophages was visualized under fluorescent microscopy and live-cell imaging and analyzed through flow cytometry analysis. Cytokine production in dendritic cells (DCs) infected by fungal cells was measured by xMAP technology and the transcriptional profiles of murine macrophages-infected by different mutants were compared.ResultsWe find that phosphopeptidomannan (PPM) reduction in goa1Δ and nuo1Δ and phospholipomannan (PLM) reduction in nuo2Δ correlate with massive inhibition of cytokine. PPM loss in nuo1Δ or goa1Δ fails to promote phagocytosis but promotes opsonized neutrophil killing. The cause of PPM insufficiency results from reduced phosphorylation of the Cek1 MAPK in goa1Δ and nuo1Δ. In contrast other three mutants, phagocytosis and cytokine production of ndh51Δ more resemble WT cells, which have shown an ∼ 30% glucan reduction due to a defective Mek1 MAPK response. The divergent immune responses to these CI mutants are shown at the transcriptional level in infected macrophages. We noted that those well-characterized host receptors such as dectins and TLR2/4 for PPM, PLM, and glucan ligands are not significantly affected at 1 h post-infection. However, the scavenger receptor CD36, integrin ICAM, and growth factor receptors are downregulated along with a generally downregulated endocytosis and antigen processing/presentation. In addition, the host metabolic processes, oxidative stress-induced senescence, apoptosis, and signaling pathways such as Ras1/Erk5, the cAMP/CREB, and TLR9 pathway, are each individually affected in the host cells.ConclusionWe speculate that mitochondrial signals of fungal origin may also be sensed by the host immune cells to coordinate the immune responses together with cell replication and metabolism during the early stage of infection.

Polydopamine encapsulated new indocyanine green theranostic nanoparticles for enhanced photothermal therapy in cervical cancer HeLa cells.

Photothermal therapy (PTT) has attracted extensive attention in cancer treatment due to its non-invasiveness, high efficiency, and repeatability in recent years. Photothermal agents (PTAs) are the key factor for PTT. Recently, although an increasing number of PTAs have been developed, there is still a great demand for optimized photothermal nanoparticles (NPs) with low toxicity, bio-safety and stability. Herein, new indocyanine green (IR820) with near-infrared (NIR:700–1,700 nm) fluorescence emission was selected as a photothermal agent (PTA). To enhance the PTT property, IR820 was encapsulated with another kind of PTA, polydopamine (PDA) under alkaline conditions. Furthermore, to improve the biocompatibility of the NPs, methoxy polyethylene glycol amine (mPEG-NH2) was modified via a Michael addition to form a novel kind of IR820@PDA@PEG NPs. After detailed characterization and analysis, the obtained IR820@PDA@PEG NPs showed a spherical shape with an average diameter of ∼159.6 nm. Meanwhile, the formed IR820@PDA@PEG NPs exhibited better photostability and lower cytotoxicity than free IR820 molecules. The photothermal performance of IR820@PDA@PEG NPs was further analyzed in vitro, and the temperature of IR820@PDA@PEG NPs (100 μg/ml) reached 54.8°C under 793 nm laser irradiation. Afterwards, the cellular uptake of IR820@PDA@PEG NPs was evaluated via confocal laser scanning fluorescence microscopic imaging. Then, PTT experiments on HeLa cells demonstrated that IR820@PDA@PEG NPs can hyperthermal ablate cancer cells (∼49.1%) under 793 nm laser irradiation. Therefore, IR820@PDA@PEG NPs would be a promising PTA for the treatment of cervical cancer HeLa cells.